-
1
-
-
85054621623
-
Google’s AI eye doctor gets ready to go to work in India
-
6 August
-
Simonite, T. Google’s AI eye doctor gets ready to go to work in India. WIRED (6 August 2017)
-
(2017)
WIRED
-
-
Simonite, T.1
-
2
-
-
85132189046
-
Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss
-
Lee, R., Wong, T. Y. & Sabanayagam, C. Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss. Eye Vis. 2, 17 (2015)
-
(2015)
Eye Vis.
, vol.2
-
-
Lee, R.1
Wong, T.Y.2
Sabanayagam, C.3
-
3
-
-
0036326496
-
The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography
-
PID: 12140027
-
Lin, D. Y., Blumenkranz, M. S., Brothers, R. J. & Grosvenor, D. M. The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography. Am. J. Ophthalmol. 134, 204–213 (2002)
-
(2002)
Am. J. Ophthalmol.
, vol.134
, pp. 204-213
-
-
Lin, D.Y.1
Blumenkranz, M.S.2
Brothers, R.J.3
Grosvenor, D.M.4
-
4
-
-
84866358054
-
The worldwide epidemic of diabetic retinopathy
-
PID: 22944754
-
Zheng, Y., He, M. & Congdon, N. The worldwide epidemic of diabetic retinopathy. Indian J. Ophthalmol. 60, 428–431 (2012)
-
(2012)
Indian J. Ophthalmol.
, vol.60
, pp. 428-431
-
-
Zheng, Y.1
He, M.2
Congdon, N.3
-
5
-
-
85007529863
-
Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
-
Gulshan, V. et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 316, 2402–2410 (2016)
-
(2016)
JAMA
, vol.316
, pp. 2402-2410
-
-
Gulshan, V.1
-
6
-
-
85042201755
-
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning
-
Poplin, R. et al. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nat. Biomed. Eng. 2, 158–164 (2018)
-
(2018)
Nat. Biomed. Eng.
, vol.2
, pp. 158-164
-
-
Poplin, R.1
-
7
-
-
85095168170
-
Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices
-
Abràmoff, M. D., Lavin, P. T., Birch, M., Shah, N. & Folk, J. C. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices. NPJ Digit. Med. 1, 39 (2018)
-
(2018)
NPJ Digit. Med.
, vol.1
, pp. 39
-
-
Abràmoff, M.D.1
Lavin, P.T.2
Birch, M.3
Shah, N.4
Folk, J.C.5
-
9
-
-
84876231242
-
-
Curran Associates, Nevada
-
Krizhevsky, A., Sutskever, I. & Hinton, G. E. in Advances in Neural Information Processing Systems 1097–1105 (Curran Associates, Nevada, 2012)
-
(2012)
Advances in Neural Information Processing Systems
, pp. 1097-1105
-
-
Krizhevsky, A.1
Sutskever, I.2
Hinton, G.E.3
-
11
-
-
0033908714
-
Knowledge-based ECG interpretation: a critical review
-
Kundu, M., Nasipuri, M. & Basu, D. K. Knowledge-based ECG interpretation: a critical review. Pattern Recognit. 33, 351–373 (2000)
-
(2000)
Pattern Recognit.
, vol.33
, pp. 351-373
-
-
Kundu, M.1
Nasipuri, M.2
Basu, D.K.3
-
12
-
-
85007524689
-
Adapting to artificial intelligence: radiologists and pathologists as information specialists
-
PID: 27898975
-
Jha, S. & Topol, E. J. Adapting to artificial intelligence: radiologists and pathologists as information specialists. JAMA 316, 2353–2354 (2016)
-
(2016)
JAMA
, vol.316
, pp. 2353-2354
-
-
Jha, S.1
Topol, E.J.2
-
13
-
-
0033569406
-
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring
-
COI: 1:CAS:528:DyaK1MXmvVOhu7g%3D, PID: 10521349
-
Golub, T. R. et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531–537 (1999)
-
(1999)
Science
, vol.286
, pp. 531-537
-
-
Golub, T.R.1
-
14
-
-
12444320350
-
Gene selection from microarray data for cancer classification—a machine learning approach
-
PID: 15680584
-
Wang, Y. et al. Gene selection from microarray data for cancer classification—a machine learning approach. Comput. Biol. Chem. 29, 37–46 (2005)
-
(2005)
Comput. Biol. Chem.
, vol.29
, pp. 37-46
-
-
Wang, Y.1
-
15
-
-
84981313253
-
Predicting ovarian cancer patients’ clinical response to platinum-based chemotherapy by their tumor proteomic signatures
-
COI: 1:CAS:528:DC%2BC28XhtVSrsrzI, PID: 27312948
-
Yu, K. H. et al. Predicting ovarian cancer patients’ clinical response to platinum-based chemotherapy by their tumor proteomic signatures. J. Proteome Res. 15, 2455–2465 (2016)
-
(2016)
J. Proteome Res.
, vol.15
, pp. 2455-2465
-
-
Yu, K.H.1
-
16
-
-
85040588585
-
Omics AnalySIs System for PRecision Oncology (OASISPRO): a web-based omics analysis tool for clinical phenotype prediction
-
Yu, K. H. et al. Omics AnalySIs System for PRecision Oncology (OASISPRO): a web-based omics analysis tool for clinical phenotype prediction. Bioinformatics 34, 319–320 (2017)
-
(2017)
Bioinformatics
, vol.34
, pp. 319-320
-
-
Yu, K.H.1
-
17
-
-
84922335093
-
The automated lab
-
COI: 1:CAS:528:DC%2BC2cXitVakt7%2FM, PID: 25471888
-
Check Hayden, E. The automated lab. Nature 516, 131–132 (2014)
-
(2014)
Nature
, vol.516
, pp. 131-132
-
-
Check Hayden, E.1
-
18
-
-
0028367412
-
Medical diagnostic decision support systems–past, present, and future: a threaded bibliography and brief commentary
-
COI: 1:STN:280:DyaK2M3js1Wnsw%3D%3D, PID: 7719792
-
Miller, R. A. Medical diagnostic decision support systems–past, present, and future: a threaded bibliography and brief commentary. J. Am. Med. Inform. Assoc. 1, 8–27 (1994)
-
(1994)
J. Am. Med. Inform. Assoc.
, vol.1
, pp. 8-27
-
-
Miller, R.A.1
-
19
-
-
84974655258
-
-
eds Shortliffe, E. H. & Cimino, J. J, Springer, London
-
Musen, M. A., Middleton, B. & Greenes, R. A. in Biomedical Informatics (eds Shortliffe, E. H. & Cimino, J. J.) 643–674 (Springer, London, 2014)
-
(2014)
Biomedical Informatics
, pp. 643-674
-
-
Musen, M.A.1
Middleton, B.2
Greenes, R.A.3
-
21
-
-
0023949557
-
Artificial intelligence in medical diagnosis
-
COI: 1:STN:280:DyaL1c7gsFShtQ%3D%3D, PID: 3276267
-
Szolovits, P., Patil, R. S. & Schwartz, W. B. Artificial intelligence in medical diagnosis. Ann. Intern. Med. 108, 80–87 (1988)
-
(1988)
Ann. Intern. Med.
, vol.108
, pp. 80-87
-
-
Szolovits, P.1
Patil, R.S.2
Schwartz, W.B.3
-
22
-
-
0015320133
-
Computer-aided diagnosis of acute abdominal pain
-
PID: 4552594
-
de Dombal, F. T., Leaper, D. J., Staniland, J. R., McCann, A. P. & Horrocks, J. C. Computer-aided diagnosis of acute abdominal pain. Br. Med. J. 2, 9–13 (1972)
-
(1972)
Br. Med. J.
, vol.2
, pp. 9-13
-
-
de Dombal, F.T.1
Leaper, D.J.2
Staniland, J.R.3
McCann, A.P.4
Horrocks, J.C.5
-
23
-
-
84886614002
-
Computer-based consultations in clinical therapeutics: explanation and rule acquisition capabilities of the MYCIN system
-
COI: 1:STN:280:DyaE28%2Fgt1eitQ%3D%3D, PID: 1157471
-
Shortliffe, E. H. et al. Computer-based consultations in clinical therapeutics: explanation and rule acquisition capabilities of the MYCIN system. Comput. Biomed. Res. 8, 303–320 (1975)
-
(1975)
Comput. Biomed. Res.
, vol.8
, pp. 303-320
-
-
Shortliffe, E.H.1
-
24
-
-
85047694791
-
DXplain
-
COI: 1:STN:280:DyaL2s3is1KnsQ%3D%3D, PID: 3295316
-
Barnett, G. O., Cimino, J. J., Hupp, J. A. & Hoffer, E. P. DXplain. An evolving diagnostic decision-support system. JAMA 258, 67–74 (1987)
-
(1987)
JAMA
, vol.258
, Issue.1
, pp. 67
-
-
Barnett, G.O.1
-
25
-
-
0022886346
-
The INTERNIST-1/QUICK MEDICAL REFERENCE Project — status report
-
Miller, R. A., McNeil, M. A., Challinor, S. M., Masarie, F. E. Jr & Myers, J. D. The INTERNIST-1/QUICK MEDICAL REFERENCE Project — status report. Western J. Med. 145, 816–822 (1986)
-
(1986)
Western J. Med.
, vol.145
, pp. 816-822
-
-
Miller, R.A.1
McNeil, M.A.2
Challinormasarie, S.M.3
Myers, J.D.4
-
26
-
-
0028234740
-
Performance of four computer-based diagnostic systems
-
COI: 1:STN:280:DyaK2c3kslCrtA%3D%3D, PID: 8190157
-
Berner, E. S. et al. Performance of four computer-based diagnostic systems. N. Engl. J. Med. 330, 1792–1796 (1994)
-
(1994)
N. Engl. J. Med.
, vol.330
, pp. 1792-1796
-
-
Berner, E.S.1
-
27
-
-
0018000788
-
Categorical and probabilistic reasoning in medical diagnosis
-
Szolovits, P. & Pauker, S. G. Categorical and probabilistic reasoning in medical diagnosis. Artif. Intell. 11, 115–144 (1978)
-
(1978)
Artif. Intell.
, vol.11
, pp. 115-144
-
-
Szolovits, P.1
Pauker, S.G.2
-
28
-
-
84947466043
-
Machine learning in medicine
-
PID: 5831252
-
Deo, R. C. Machine learning in medicine. Circulation 132, 1920–1930 (2015)
-
(2015)
Circulation
, vol.132
, pp. 1920-1930
-
-
Deo, R.C.1
-
29
-
-
84982823011
-
Omics profiling in precision oncology
-
COI: 1:CAS:528:DC%2BC28Xht1OktbvN, PID: 27099341
-
Yu, K. H. & Snyder, M. Omics profiling in precision oncology. Mol. Cell. Proteomics 15, 2525–2536 (2016)
-
(2016)
Mol. Cell. Proteomics
, vol.15
, pp. 2525-2536
-
-
Yu, K.H.1
Snyder, M.2
-
30
-
-
85019160724
-
Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics
-
Roberts, K. et al. Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics. J. Am. Med. Inform. Assoc. 24, 185–190 (2017)
-
(2017)
J. Am. Med. Inform. Assoc.
, vol.24
, pp. 185-190
-
-
Roberts, K.1
-
31
-
-
85054604733
-
-
ALPHA (Google Cloud); https://cloud.google.com/automl/
-
-
-
-
32
-
-
84944735469
-
-
MIT Press, Cambridge
-
Goodfellow, I., Bengio, Y., Courville, A. & Bengio, Y. Deep Learning 1 (MIT Press, Cambridge, 2016)
-
(2016)
Deep Learning
-
-
Goodfellow, I.1
Bengio, Y.2
Courville, A.3
Bengio, Y.4
-
35
-
-
85007559018
-
Translating artificial intelligence into clinical care
-
PID: 27898974
-
Beam, A. L. & Kohane, I. S. Translating artificial intelligence into clinical care. JAMA 316, 2368–2369 (2016)
-
(2016)
JAMA
, vol.316
, pp. 2368-2369
-
-
Beam, A.L.1
Kohane, I.S.2
-
36
-
-
79954500285
-
Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software
-
COI: 1:CAS:528:DC%2BC3MXksFKlu78%3D, PID: 21349861
-
Kamentsky, L. et al. Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software. Bioinformatics 27, 1179–1180 (2011)
-
(2011)
Bioinformatics
, vol.27
, pp. 1179-1180
-
-
Kamentsky, L.1
-
37
-
-
85045190865
-
Opportunities and obstacles for deep learning in biology and medicine
-
Ching, T. et al. Opportunities and obstacles for deep learning in biology and medicine. J. R. Soc. Interface 15, 20170387 (2018)
-
(2018)
J. R. Soc. Interface
, vol.15
, pp. 20170387
-
-
Ching, T.1
-
38
-
-
84934922563
-
The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge
-
Tomczak, K., Czerwinska, P. & Wiznerowicz, M. The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemp. Oncol. 19, 68–77 (2015)
-
(2015)
Contemp. Oncol.
, vol.19
, pp. 68-77
-
-
Tomczak, K.1
Czerwinska, P.2
Wiznerowicz, M.3
-
39
-
-
84926430250
-
UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age
-
PID: 25826379
-
Sudlow, C. et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015)
-
(2015)
PLoS Med.
, vol.12
-
-
Sudlow, C.1
-
40
-
-
84863198481
-
Annotated high-throughput microscopy image sets for validation
-
COI: 1:CAS:528:DC%2BC38XhtVKnt73I, PID: 22743765
-
Ljosa, V., Sokolnicki, K. L. & Carpenter, A. E. Annotated high-throughput microscopy image sets for validation. Nat. Methods 9, 637 (2012)
-
(2012)
Nat. Methods
, vol.9
, pp. 637
-
-
Ljosa, V.1
Sokolnicki, K.L.2
Carpenter, A.E.3
-
41
-
-
85026475117
-
The image data resource: a bioimage data integration and publication platform
-
COI: 1:CAS:528:DC%2BC2sXhtVantL%2FN, PID: 28775673
-
Williams, E. et al. The image data resource: a bioimage data integration and publication platform. Nat. Methods 14, 775–781 (2017)
-
(2017)
Nat. Methods
, vol.14
, pp. 775-781
-
-
Williams, E.1
-
42
-
-
46449113799
-
Electronic health records in ambulatory care–a national survey of physicians
-
COI: 1:CAS:528:DC%2BD1cXotFSisLc%3D, PID: 18565855
-
DesRoches, C. M. et al. Electronic health records in ambulatory care–a national survey of physicians. N. Engl. J. Med. 359, 50–60 (2008)
-
(2008)
N. Engl. J. Med.
, vol.359
, pp. 50-60
-
-
DesRoches, C.M.1
-
43
-
-
84884221972
-
Office-based physicians are responding to incentives and assistance by adopting and using electronic health records
-
Hsiao, C. J. et al. Office-based physicians are responding to incentives and assistance by adopting and using electronic health records. Health Aff. 32, 1470–1477 (2013)
-
(2013)
Health Aff.
, vol.32
, pp. 1470-1477
-
-
Hsiao, C.J.1
-
44
-
-
85016143105
-
Dermatologist-level classification of skin cancer with deep neural networks
-
COI: 1:CAS:528:DC%2BC2sXhsFGltrY%3D
-
Esteva, A. et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 542, 115–118 (2017)
-
(2017)
Nature
, vol.542
, pp. 115-118
-
-
Esteva, A.1
-
45
-
-
81055146760
-
Systematic analysis of breast cancer morphology uncovers stromal features associated with survival
-
PID: 22072638
-
Beck, A. H. et al. Systematic analysis of breast cancer morphology uncovers stromal features associated with survival. Sci. Transl. Med. 3, 108ra113 (2011)
-
(2011)
Sci. Transl. Med.
, vol.3
, pp. 108ra113
-
-
Beck, A.H.1
-
46
-
-
84982218412
-
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
-
COI: 1:CAS:528:DC%2BC28Xhtlylsb7E, PID: 27527408
-
Yu, K. H. et al. Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features. Nat. Commun. 7, 12474 (2016)
-
(2016)
Nat. Commun.
, vol.7
-
-
Yu, K.H.1
-
47
-
-
84969980426
-
Supervised autonomous robotic soft tissue surgery
-
Shademan, A. et al. Supervised autonomous robotic soft tissue surgery. Sci. Transl. Med. 8, 337ra364 (2016)
-
(2016)
Sci. Transl. Med.
, vol.8
, pp. 337ra364
-
-
Shademan, A.1
-
49
-
-
0000101639
-
Computer diagnosis of primary bone tumors: a preliminary report
-
Lodwick, G. S., Haun, C. L., Smith, W. E., Keller, R. F. & Robertson, E. D. Computer diagnosis of primary bone tumors: a preliminary report. Radiology 80, 273–275 (1963)
-
(1963)
Radiology
, vol.80
, pp. 273-275
-
-
Lodwick, G.S.1
Haun, C.L.2
Smith, W.E.3
Keller, R.F.4
Robertson, E.D.5
-
50
-
-
84943812643
-
Off-the-shelf convolutional neural network features for pulmonary nodule detection in computed tomography scans
-
IEEE
-
van Ginneken, B., Setio, A. A., Jacobs, C. & Ciompi, F. Off-the-shelf convolutional neural network features for pulmonary nodule detection in computed tomography scans. In IEEE 12th International Symposium Biomedical Imaging (ISBI) 286–289 (IEEE, 2015)
-
(2015)
IEEE 12Th International Symposium Biomedical Imaging (ISBI)
, pp. 286-289
-
-
van Ginneken, B.1
Setio, A.A.2
Jacobs, C.3
Ciompi, F.4
-
51
-
-
85025112337
-
Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks
-
PID: 28436741
-
Lakhani, P. & Sundaram, B. Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks. Radiology 284, 574–582 (2017)
-
(2017)
Radiology
, vol.284
, pp. 574-582
-
-
Lakhani, P.1
Sundaram, B.2
-
55
-
-
85000788384
-
Mass detection in digital breast tomosynthesis: deep convolutional neural network with transfer learning from mammography
-
PID: 27908154
-
Samala, R. K. et al. Mass detection in digital breast tomosynthesis: deep convolutional neural network with transfer learning from mammography. Med. Phys. 43, 6654–6666 (2016)
-
(2016)
Med. Phys.
, vol.43
, pp. 6654-6666
-
-
Samala, R.K.1
-
56
-
-
84953238909
-
Convolutional neural networks for mammography mass lesion classification
-
IEEE
-
Arevalo, J., González, F. A., Ramos-Pollán, R., Oliveira, J. L. & Lopez, M. A. G. Convolutional neural networks for mammography mass lesion classification. In IEEE 37th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC) 797–800 (IEEE, 2015)
-
(2015)
IEEE 37Th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC)
, pp. 797-800
-
-
Arevalo, J.1
González, F.A.2
Ramos-Pollán, R.3
Oliveira, J.L.4
Lopez, M.A.G.5
-
57
-
-
85054698110
-
-
510(k) Premarket Notification, FDA
-
510(k) Premarket Notification (FDA, 2017); https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K163253
-
(2017)
-
-
-
58
-
-
85038816366
-
First FDA approval for clinical cloud-based deep learning in healthcare
-
20 January
-
Marr, B. First FDA approval for clinical cloud-based deep learning in healthcare. Forbes (20 January 2017)
-
(2017)
Forbes
-
-
Marr, B.1
-
59
-
-
24044498349
-
ABCDE—an evolving concept in the early detection of melanoma
-
PID: 16103334
-
Rigel, D. S., Friedman, R. J., Kopf, A. W. & Polsky, D. ABCDE—an evolving concept in the early detection of melanoma. Arch. Dermatol. 141, 1032–1034 (2005)
-
(2005)
Arch. Dermatol.
, vol.141
, pp. 1032-1034
-
-
Rigel, D.S.1
Friedman, R.J.2
Kopf, A.W.3
Polsky, D.4
-
60
-
-
0031819345
-
Semiological value of ABCDE criteria in the diagnosis of cutaneous pigmented tumors
-
COI: 1:STN:280:DyaK1cznslaqtw%3D%3D, PID: 9693179
-
Thomas, L. et al. Semiological value of ABCDE criteria in the diagnosis of cutaneous pigmented tumors. Dermatology 197, 11–17 (1998)
-
(1998)
Dermatology
, vol.197
, pp. 11-17
-
-
Thomas, L.1
-
61
-
-
0028105994
-
Neural network diagnosis of malignant melanoma from color images
-
COI: 1:STN:280:DyaK2M%2FkvVCisQ%3D%3D, PID: 7959811
-
Ercal, F., Chawla, A., Stoecker, W. V., Lee, H. C. & Moss, R. H. Neural network diagnosis of malignant melanoma from color images. IEEE Trans. Biomed. Eng. 41, 837–845 (1994)
-
(1994)
IEEE Trans. Biomed. Eng.
, vol.41
, pp. 837-845
-
-
Ercal, F.1
Chawla, A.2
Stoecker, W.V.3
Lee, H.C.4
Moss, R.H.5
-
62
-
-
84876128311
-
Diagnostic inaccuracy of smartphone applications for melanoma detection
-
PID: 23325302
-
Wolf, J. A. et al. Diagnostic inaccuracy of smartphone applications for melanoma detection. JAMA Dermatol. 149, 422–426 (2013)
-
(2013)
JAMA Dermatol.
, vol.149
, pp. 422-426
-
-
Wolf, J.A.1
-
63
-
-
84962170796
-
Fundus photography in the 21st century — a review of recent technological advances and their implications for worldwide healthcare
-
PID: 26308281
-
Panwar, N. et al. Fundus photography in the 21st century — a review of recent technological advances and their implications for worldwide healthcare. Telemed. J. E. Health 22, 198–208 (2016)
-
(2016)
Telemed. J. E. Health
, vol.22
, pp. 198-208
-
-
Panwar, N.1
-
64
-
-
85009192407
-
10. Microvascular complications and foot care
-
American Diabetes Association. 10. Microvascular complications and foot care. Diabetes Care 40, 88–98 (2017)
-
(2017)
Diabetes Care
, vol.40
, pp. 88-98
-
-
-
65
-
-
84941702063
-
Prevalence of and trends in diabetes among adults in the United States, 1988–2012
-
COI: 1:CAS:528:DC%2BC28XkslKjtA%3D%3D, PID: 26348752
-
Menke, A., Casagrande, S., Geiss, L. & Cowie, C. C. Prevalence of and trends in diabetes among adults in the United States, 1988–2012. JAMA 314, 1021–1029 (2015)
-
(2015)
JAMA
, vol.314
, pp. 1021-1029
-
-
Menke, A.1
Casagrande, S.2
Geiss, L.3
Cowie, C.C.4
-
66
-
-
84990193991
-
Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning
-
Abràmoff, M. D. et al. Improved automated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning. Investigative Opthalmology Visual Sci. 57, 5200–5206 (2016)
-
(2016)
Investigative Opthalmology & Visual Science
, vol.57
, Issue.13
, pp. 5200
-
-
Abràmoff, M.D.1
Lou, Y.2
Erginay, A.3
Clarida, W.4
Amelon, R.5
Folk, J.C.6
Niemeijer, M.7
-
67
-
-
0031046295
-
Pathologic diagnosis as the gold standard
-
COI: 1:STN:280:DyaK2s7nslWmsg%3D%3D, PID: 9024702
-
Rorke, L. B. Pathologic diagnosis as the gold standard. Cancer 79, 665–667 (1997)
-
(1997)
Cancer
, vol.79
, pp. 665-667
-
-
Rorke, L.B.1
-
68
-
-
0035525289
-
Microarray and histopathological analysis of tumours: the future and the past?
-
COI: 1:CAS:528:DC%2BD38XlvF2qsLs%3D, PID: 11905806
-
Lakhani, S. R. & Ashworth, A. Microarray and histopathological analysis of tumours: the future and the past? Nat. Rev. Cancer 1, 151–157 (2001)
-
(2001)
Nat. Rev. Cancer
, vol.1
, pp. 151-157
-
-
Lakhani, S.R.1
Ashworth, A.2
-
69
-
-
0037145318
-
Automated diagnosis of pigmented skin lesions
-
COI: 1:CAS:528:DC%2BD38Xns1eqsrg%3D, PID: 12237900
-
Rubegni, P. et al. Automated diagnosis of pigmented skin lesions. Int. J. Cancer 101, 576–580 (2002)
-
(2002)
Int. J. Cancer
, vol.101
, pp. 576-580
-
-
Rubegni, P.1
-
70
-
-
33644759126
-
Diagnostic agreement in the histopathological evaluation of lung cancer tissue in a population-based case-control study
-
PID: 16476504
-
Stang, A. et al. Diagnostic agreement in the histopathological evaluation of lung cancer tissue in a population-based case-control study. Lung Cancer 52, 29–36 (2006)
-
(2006)
Lung Cancer
, vol.52
, pp. 29-36
-
-
Stang, A.1
-
71
-
-
85033780544
-
Association of omics features with histopathology patterns in lung adenocarcinoma
-
COI: 1:CAS:528:DC%2BC1cXhs1OltQ%3D%3D, PID: 29153840
-
Yu, K. H. et al. Association of omics features with histopathology patterns in lung adenocarcinoma. Cell Syst. 5, 620–627 (2017)
-
(2017)
Cell Syst.
, vol.5
, pp. 620-627
-
-
Yu, K.H.1
-
72
-
-
84970028091
-
Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis
-
COI: 1:CAS:528:DC%2BC28XosVSht70%3D, PID: 27212078
-
Litjens, G. et al. Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis. Sci. Rep. 6, 26286 (2016)
-
(2016)
Sci. Rep.
, vol.6
-
-
Litjens, G.1
-
73
-
-
85054606390
-
Machine learning detection of breast cancer lymph node metastases
-
Bejnordi, B. E. et al. Machine learning detection of breast cancer lymph node metastases. JAMA 318, 2199–2210 (2017)
-
(2017)
JAMA
, vol.318
, pp. 2199-2210
-
-
Bejnordi, B.E.1
-
74
-
-
84885899176
-
-
eds Mori, K. et al, Springer, Berlin, Heidelberg
-
Cireşan, D. C., Giusti, A., Gambardella, L. M. & Schmidhuber, J. in Medical Image Computing and Computer-Assisted Intervention — MICCAI 2013 (eds Mori, K. et al.) 411–418 (Springer, Berlin, Heidelberg, 2013)
-
(2013)
Medical Image Computing and Computer-Assisted Intervention — MICCAI 2013
, pp. 411-418
-
-
Cireşan, D.C.1
Giusti, A.2
Gambardella, L.M.3
Schmidhuber, J.4
-
75
-
-
85053806353
-
Live-cell phenotypic-biomarker microfluidic assay for the risk stratification of cancer patients via machine learning
-
Manak, M. S. et al. Live-cell phenotypic-biomarker microfluidic assay for the risk stratification of cancer patients via machine learning. Nat. Biomed. Eng. 10.1038/s41551-018-0285-z (2018)
-
(2018)
Nature Biomedical Engineering
, vol.2
, Issue.10
, pp. 761-772
-
-
Manak, M.S.1
Varsanik, J.S.2
Hogan, B.J.3
Whitfield, M.J.4
Su, W.R.5
Joshi, N.6
Steinke, N.7
Min, A.8
Berger, D.9
Saphirstein, R.J.10
Dixit, G.11
Meyyappan, T.12
Chu, H.-M.13
Knopf, K.B.14
Albala, D.M.15
Sant, G.R.16
Chander, A.C.17
-
76
-
-
84892765381
-
Pathologist workforce in the United States: I. Development of a predictive model to examine factors influencing supply
-
PID: 23738764
-
Robboy, S. J. et al. Pathologist workforce in the United States: I. Development of a predictive model to examine factors influencing supply. Arch. Pathol. Lab. Med. 137, 1723–1732 (2013)
-
(2013)
Arch. Pathol. Lab. Med.
, vol.137
, pp. 1723-1732
-
-
Robboy, S.J.1
-
77
-
-
85026529300
-
A survey on deep learning in medical image analysis
-
PID: 28778026
-
Litjens, G. et al. A survey on deep learning in medical image analysis. Med. Image Anal. 42, 60–88 (2017)
-
(2017)
Med. Image Anal.
, vol.42
, pp. 60-88
-
-
Litjens, G.1
-
78
-
-
84928997067
-
DANN: a deep learning approach for annotating the pathogenicity of genetic variants
-
COI: 1:CAS:528:DC%2BC28Xht1GntLfP, PID: 25338716
-
Quang, D., Chen, Y. & Xie, X. DANN: a deep learning approach for annotating the pathogenicity of genetic variants. Bioinformatics 31, 761–763 (2015)
-
(2015)
Bioinformatics
, vol.31
, pp. 761-763
-
-
Quang, D.1
Chen, Y.2
Xie, X.3
-
79
-
-
84976413226
-
DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences
-
PID: 27084946
-
Quang, D. & Xie, X. DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences. Nucleic Acids Res. 44, e107 (2016)
-
(2016)
Nucleic Acids Research
, vol.44
, Issue.11
, pp. e107
-
-
Quang, D.1
Xie, X.2
-
82
-
-
85011690505
-
Next-generation sequencing in oncology: genetic diagnosis, risk prediction and cancer classification
-
Kamps, R. et al. Next-generation sequencing in oncology: genetic diagnosis, risk prediction and cancer classification. Int. J. Mol. Sci. 18, 308 (2017)
-
(2017)
Int. J. Mol. Sci.
, vol.18
, pp. 308
-
-
Kamps, R.1
-
83
-
-
77958449045
-
Stable feature selection for biomarker discovery
-
COI: 1:CAS:528:DC%2BC3cXhtlens7zN, PID: 20702140
-
He, Z. & Yu, W. Stable feature selection for biomarker discovery. Comput. Biol. Chem. 34, 215–225 (2010)
-
(2010)
Comput. Biol. Chem.
, vol.34
, pp. 215-225
-
-
He, Z.1
Yu, W.2
-
84
-
-
4143067096
-
Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer
-
COI: 1:CAS:528:DC%2BD2cXmslaks7Y%3D, PID: 15313933
-
Zhang, Z. et al. Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Res. 64, 5882–5890 (2004)
-
(2004)
Cancer Res.
, vol.64
, pp. 5882-5890
-
-
Zhang, Z.1
-
85
-
-
84939808101
-
Development and verification of the PAM50-based Prosigna breast cancer gene signature assay
-
PID: 26297356
-
Wallden, B. et al. Development and verification of the PAM50-based Prosigna breast cancer gene signature assay. BMC Med. Genomics 8, 54 (2015)
-
(2015)
BMC Med. Genomics
, vol.8
-
-
Wallden, B.1
-
86
-
-
84978062345
-
Robust classification of bacterial and viral infections via integrated host gene expression diagnostics
-
Sweeney, T. E., Wong, H. R. & Khatri, P. Robust classification of bacterial and viral infections via integrated host gene expression diagnostics. Sci. Transl. Med. 8, 346ra391 (2016)
-
(2016)
Sci. Transl. Med.
, vol.8
, pp. 346ra391
-
-
Sweeney, T.E.1
Wong, H.R.2
Khatri, P.3
-
87
-
-
77951734507
-
Prediction of adverse pregnancy outcomes by combinations of first and second trimester biochemistry markers used in the routine prenatal screening of Down syndrome
-
PID: 20440736
-
Huang, T., Hoffman, B., Meschino, W., Kingdom, J. & Okun, N. Prediction of adverse pregnancy outcomes by combinations of first and second trimester biochemistry markers used in the routine prenatal screening of Down syndrome. Prenat. Diagn. 30, 471–477 (2010)
-
(2010)
Prenat. Diagn.
, vol.30
, pp. 471-477
-
-
Huang, T.1
Hoffman, B.2
Meschino, W.3
Kingdom, J.4
Okun, N.5
-
88
-
-
77952095549
-
Metastatic potential of T1 breast cancer can be predicted by the 70-gene MammaPrint signature
-
PID: 20094918
-
Mook, S. et al. Metastatic potential of T1 breast cancer can be predicted by the 70-gene MammaPrint signature. Ann. Surg. Oncol. 17, 1406–1413 (2010)
-
(2010)
Ann. Surg. Oncol.
, vol.17
, pp. 1406-1413
-
-
Mook, S.1
-
89
-
-
85025679781
-
Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation
-
Farina, D. et al. Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation. Nat. Biomed. Eng. 1, 0025 (2017)
-
(2017)
Nat. Biomed. Eng.
, vol.1
, pp. 0025
-
-
Farina, D.1
-
90
-
-
85018521903
-
Artificial intelligence (AI) systems for interpreting complex medical datasets
-
COI: 1:STN:280:DC%2BC1c3lt1Wktw%3D%3D, PID: 28182259
-
Altman, R. B. Artificial intelligence (AI) systems for interpreting complex medical datasets. Clin. Pharmacol. Ther. 101, 585–586 (2017)
-
(2017)
Clin. Pharmacol. Ther.
, vol.101
, pp. 585-586
-
-
Altman, R.B.1
-
91
-
-
84979055388
-
Real-time prediction of mortality, readmission, and length of stay using electronic health record data
-
PID: 26374704
-
Cai, X. et al. Real-time prediction of mortality, readmission, and length of stay using electronic health record data. J. Am. Med. Inform. Assoc. 23, 553–561 (2016)
-
(2016)
J. Am. Med. Inform. Assoc.
, vol.23
, pp. 553-561
-
-
Cai, X.1
-
92
-
-
84983219407
-
Short-term mortality prediction for elderly patients using medicare claims data
-
PID: 28018571
-
Makar, M., Ghassemi, M., Cutler, D. M. & Obermeyer, Z. Short-term mortality prediction for elderly patients using medicare claims data. Int. J. Mach. Learn. Comput. 5, 192–197 (2015)
-
(2015)
Int. J. Mach. Learn. Comput.
, vol.5
, pp. 192-197
-
-
Makar, M.1
Ghassemi, M.2
Cutler, D.M.3
Obermeyer, Z.4
-
93
-
-
84864609657
-
A clinical decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy
-
PID: 22690950
-
Ng, T., Chew, L. & Yap, C. W. A clinical decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy. J. Palliat. Med. 15, 863–869 (2012)
-
(2012)
J. Palliat. Med.
, vol.15
, pp. 863-869
-
-
Ng, T.1
Chew, L.2
Yap, C.W.3
-
94
-
-
77951625860
-
A machine learning-based approach to prognostic analysis of thoracic transplantations
-
PID: 20153956
-
Delen, D., Oztekin, A. & Kong, Z. J. A machine learning-based approach to prognostic analysis of thoracic transplantations. Artif. Intell. Med. 49, 33–42 (2010)
-
(2010)
Artif. Intell. Med.
, vol.49
, pp. 33-42
-
-
Delen, D.1
Oztekin, A.2
Kong, Z.J.3
-
95
-
-
84860555453
-
Predicting cardiac arrest on the wards: a nested case-control study
-
PID: 22052772
-
Churpek, M. M. et al. Predicting cardiac arrest on the wards: a nested case-control study. Chest 141, 1170–1176 (2012)
-
(2012)
Chest
, vol.141
, pp. 1170-1176
-
-
Churpek, M.M.1
-
96
-
-
84921697939
-
Multicenter development and validation of a risk stratification tool for ward patients
-
PID: 25089847
-
Churpek, M. M. et al. Multicenter development and validation of a risk stratification tool for ward patients. Am. J. Respir. Crit. Care Med. 190, 649–655 (2014)
-
(2014)
Am. J. Respir. Crit. Care Med.
, vol.190
, pp. 649-655
-
-
Churpek, M.M.1
-
97
-
-
85054648327
-
Explainable machine-learning predictions for the prevention of hypoxaemia during surgery
-
Lundberg, S. M. et al. Explainable machine-learning predictions for the prevention of hypoxaemia during surgery. Nat. Biomed. Eng. 10.1038/s41551-018-0304-0 (2018)
-
(2018)
Nat. Biomed. Eng.
-
-
Lundberg, S.M.1
-
98
-
-
85011883613
-
Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information
-
PID: 28081144
-
Li, X. et al. Digital health: tracking physiomes and activity using wearable biosensors reveals useful health-related information. PLoS Biol. 15, e2001402 (2017)
-
(2017)
PLOS Biology
, vol.15
, Issue.1
-
-
Li, X.1
Dunn, J.2
Salins, D.3
Zhou, G.4
Zhou, W.5
Schüssler-Fiorenza Rose, S.M.6
Perelman, D.7
Colbert, E.8
Runge, R.9
Rego, S.10
Sonecha, R.11
Datta, S.12
McLaughlin, T.13
Snyder, M.P.14
-
99
-
-
85009999439
-
Wearable sensors for remote health monitoring
-
Majumder, S., Mondal, T. & Deen, M. J. Wearable sensors for remote health monitoring. Sensors 17, 130 (2017)
-
(2017)
Sensors
, vol.17
, pp. 130
-
-
Majumder, S.1
Mondal, T.2
Deen, M.J.3
-
100
-
-
84880315431
-
Wearable sensor network for health monitoring: the case of Parkinson disease
-
Pastorino, M., Arredondo, M., Cancela, J. & Guillen, S. Wearable sensor network for health monitoring: the case of Parkinson disease. J. Phys. Conf. Ser. 450, 012055 (2013)
-
(2013)
J. Phys. Conf. Ser.
, vol.450
, pp. 012055
-
-
Pastorino, M.1
Arredondo, M.2
Cancela, J.3
Guillen, S.4
-
101
-
-
84975143046
-
Behavior change techniques present in wearable activity trackers: a critical analysis
-
PID: 27122452
-
Mercer, K., Li, M., Giangregorio, L., Burns, C. & Grindrod, K. Behavior change techniques present in wearable activity trackers: a critical analysis. JMIR Mhealth Uhealth 4, e40 (2016)
-
(2016)
JMIR Mhealth Uhealth
, vol.4
-
-
Mercer, K.1
Li, M.2
Giangregorio, L.3
Burns, C.4
Grindrod, K.5
-
102
-
-
84906324524
-
Validation of the Fitbit One activity monitor device during treadmill walking
-
PID: 24268570
-
Takacs, J. et al. Validation of the Fitbit One activity monitor device during treadmill walking. J. Sci. Med. Sport 17, 496–500 (2014)
-
(2014)
J. Sci. Med. Sport
, vol.17
, pp. 496-500
-
-
Takacs, J.1
-
103
-
-
84960909264
-
When fitness trackers don’t ‘fit’: End-user difficulties in the assessment of personal tracking device accuracy
-
ACM
-
Yang, R., Shin, E., Newman, M. W. & Ackerman, M. S. When fitness trackers don’t ‘fit’: end-user difficulties in the assessment of personal tracking device accuracy. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing 623–634 (ACM, 2015)
-
(2015)
Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
, pp. 623-634
-
-
Yang, R.1
Shin, E.2
Newman, M.W.3
Ackerman, M.S.4
-
104
-
-
85054661620
-
Inside wearables: How the science of human behavior change offers the secret to long-term engagement
-
Endeavour Partners. Inside wearables: how the science of human behavior change offers the secret to long-term engagement. Medium https://blog.endeavour.partners/inside-wearable-how-the-science-of-human-behavior-change-offers-the-secret-to-long-term-engagement-a15b3c7d4cf3 (2017)
-
(2017)
Medium
-
-
-
105
-
-
84942888100
-
Wearables are totally failing the people who need them most
-
11 June
-
Herz, J. C. Wearables are totally failing the people who need them most. Wired (11 June 2014)
-
(2014)
Wired
-
-
Herz, J.C.1
-
106
-
-
84960855038
-
No longer wearing: Investigating the abandonment of personal health-tracking technologies on Craigslist
-
ACM
-
Clawson, J., Pater, J. A., Miller, A. D., Mynatt, E. D. & Mamykina, L. No longer wearing: investigating the abandonment of personal health-tracking technologies on Craigslist. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing 647–658 (ACM, 2015)
-
(2015)
Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
, pp. 647-658
-
-
Clawson, J.1
Pater, J.A.2
Miller, A.D.3
Mynatt, E.D.4
Mamykina, L.5
-
107
-
-
34250378327
-
Overview on robotics in the laboratory
-
COI: 1:STN:280:DC%2BD2s3kslOnsQ%3D%3D, PID: 17456291
-
Wheeler, M. J. Overview on robotics in the laboratory. Ann. Clin. Biochem. 44, 209–218 (2007)
-
(2007)
Ann. Clin. Biochem.
, vol.44
, pp. 209-218
-
-
Wheeler, M.J.1
-
108
-
-
81955160799
-
Evolution of autonomous and semi-autonomous robotic surgical systems: a review of the literature
-
COI: 1:STN:280:DC%2BC38%2Fht1Ojsw%3D%3D, PID: 21815238
-
Moustris, G. P., Hiridis, S. C., Deliparaschos, K. M. & Konstantinidis, K. M. Evolution of autonomous and semi-autonomous robotic surgical systems: a review of the literature. Int. J. Med. Robot. 7, 375–392 (2011)
-
(2011)
The International Journal of Medical Robotics and Computer Assisted Surgery
, vol.7
, Issue.4
, pp. 375-392
-
-
Moustris, G.P.1
Hiridis, S.C.2
Deliparaschos, K.M.3
Konstantinidis, K.M.4
-
109
-
-
78649330405
-
Surgical robotics: reviewing the past, analysing the present, imagining the future
-
Gomes, P. Surgical robotics: reviewing the past, analysing the present, imagining the future. Robot. Comput. Integr. Manuf. 27, 261–266 (2011)
-
(2011)
Robot. Comput. Integr. Manuf.
, vol.27
, pp. 261-266
-
-
Gomes, P.1
-
110
-
-
68549139903
-
A robot-guided minimally invasive approach for cochlear implant surgery: preliminary results of a temporal bone study
-
PID: 20033531
-
Majdani, O. et al. A robot-guided minimally invasive approach for cochlear implant surgery: preliminary results of a temporal bone study. Int. J. Comput. Assist. Radiol. Surg. 4, 475–486 (2009)
-
(2009)
Int. J. Comput. Assist. Radiol. Surg.
, vol.4
, pp. 475-486
-
-
Majdani, O.1
-
112
-
-
85044135004
-
The future of radiology augmented with artificial intelligence: a strategy for success
-
PID: 29685530
-
Liew, C. The future of radiology augmented with artificial intelligence: a strategy for success. Eur. J. Radiol. 102, 152–156 (2018)
-
(2018)
Eur. J. Radiol.
, vol.102
, pp. 152-156
-
-
Liew, C.1
-
113
-
-
85045140990
-
Artificial intelligence, machine learning and the evolution of healthcare
-
COI: 1:STN:280:DC%2BC1MbptlSrsg%3D%3D
-
Jones, L., Golan, D., Hanna, S. & Ramachandran, M. Artificial intelligence, machine learning and the evolution of healthcare: a bright future or cause for concern? Bone Joint Res. 7, 223–225 (2018)
-
(2018)
Bone & Joint Research
, vol.7
, Issue.3
, pp. 223-225
-
-
Jones, L.D.1
Golan, D.2
Hanna, S.A.3
Ramachandran, M.4
-
114
-
-
84990046464
-
Predicting the future — big data, machine learning, and clinical medicine
-
PID: 27682033
-
Obermeyer, Z. & Emanuel, E. J. Predicting the future — big data, machine learning, and clinical medicine. N. Engl. J. Med. 375, 1216–1219 (2016)
-
(2016)
N. Engl. J. Med.
, vol.375
, pp. 1216-1219
-
-
Obermeyer, Z.1
Emanuel, E.J.2
-
115
-
-
85043470011
-
Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy
-
PID: 29548646
-
Krause, J. et al. Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy. Ophthalmology 125, 1264–1272 (2018)
-
(2018)
Ophthalmology
, vol.125
, pp. 1264-1272
-
-
Krause, J.1
-
116
-
-
85037377178
-
The CALBC silver standard corpus for biomedical named entities—a study in harmonizing the contributions from four independent named entity taggers
-
Rebholz-Schuhmann, D. et al. The CALBC silver standard corpus for biomedical named entities—a study in harmonizing the contributions from four independent named entity taggers. In LREC 568–573 (2010)
-
(2010)
LREC
, pp. 568-573
-
-
Rebholz-Schuhmann, D.1
-
117
-
-
84994697920
-
PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability
-
PID: 27026615
-
Kirby, J. C. et al. PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability. J. Am. Med. Inform. Assoc. 23, 1046–1052 (2016)
-
(2016)
J. Am. Med. Inform. Assoc.
, vol.23
, pp. 1046-1052
-
-
Kirby, J.C.1
-
120
-
-
84930630277
-
Deep learning
-
COI: 1:CAS:528:DC%2BC2MXht1WlurzP, PID: 26017442
-
LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015)
-
(2015)
Nature
, vol.521
, pp. 436-444
-
-
LeCun, Y.1
Bengio, Y.2
Hinton, G.3
-
123
-
-
67649983043
-
Ethical collection, storage, and use of public health data: a proposal for a national privacy protection
-
COI: 1:CAS:528:DC%2BD1MXotF2ms7w%3D, PID: 19567443
-
Lee, L. M. & Gostin, L. O. Ethical collection, storage, and use of public health data: a proposal for a national privacy protection. JAMA 302, 82–84 (2009)
-
(2009)
JAMA
, vol.302
, pp. 82-84
-
-
Lee, L.M.1
Gostin, L.O.2
-
125
-
-
29244445108
-
HL7 Clinical Document Architecture, Release 2
-
PID: 16221939
-
Dolin, R. H. et al. HL7 Clinical Document Architecture, Release 2. J. Am. Med. Inform. Assoc. 13, 30–39 (2006)
-
(2006)
J. Am. Med. Inform. Assoc.
, vol.13
, pp. 30-39
-
-
Dolin, R.H.1
-
126
-
-
84862200972
-
Escaping the EHR trap—the future of health IT
-
&
-
Mandl, K. D. & Kohane, I. S. Escaping the EHR trap—the future of health IT. N. Engl. J. Med. 366, 2240–2242 (2012)
-
(2012)
N. Engl. J. Med.
, vol.366
, pp. 2240-2242
-
-
Mandl, K.D.1
Kohane, I.S.2
-
127
-
-
84995784013
-
SMART on FHIR: a standards-based, interoperable apps platform for electronic health records
-
PID: 26911829
-
Mandel, J. C., Kreda, D. A., Mandl, K. D., Kohane, I. S. & Ramoni, R. B. SMART on FHIR: a standards-based, interoperable apps platform for electronic health records. J. Am. Med. Inform. Assoc. 23, 899–908 (2016)
-
(2016)
J. Am. Med. Inform. Assoc.
, vol.23
, pp. 899-908
-
-
Mandel, J.C.1
Kreda, D.A.2
Mandl, K.D.3
Kohane, I.S.4
Ramoni, R.B.5
-
128
-
-
85054105226
-
All eyes are on AI
-
All eyes are on AI. Nat. Biomed. Eng. 2, 139 (2018)
-
(2018)
Nat. Biomed. Eng
, vol.2
, pp. 139
-
-
-
129
-
-
85054483394
-
Framing the challenges of artificial intelligence in medicine
-
Yu, K. H. & Kohane I. S. Framing the challenges of artificial intelligence in medicine. BMJ Qual. Safety https://doi.org/10.1136/bmjqs-2018-008551 (2018)
-
(2018)
BMJ Qual. Safety
-
-
Yu, K.H.1
Kohane, I.S.2
-
130
-
-
85041905529
-
Ethics in artificial intelligence: introduction to the special issue
-
Dignum, V. Ethics in artificial intelligence: introduction to the special issue. Ethics Inf. Technol. 20, 1–3 (2018)
-
(2018)
Ethics and Information Technology
, vol.20
, Issue.1
, pp. 1-3
-
-
Dignum, V.1
-
133
-
-
33746851719
-
Computerized provider order entry implementation: no association with increased mortality rates in an intensive care unit
-
PID: 16818577
-
Del Beccaro, M. A., Jeffries, H. E., Eisenberg, M. A. & Harry, E. D. Computerized provider order entry implementation: no association with increased mortality rates in an intensive care unit. Pediatrics 118, 290–295 (2006)
-
(2006)
Pediatrics
, vol.118
, pp. 290-295
-
-
Del Beccaro, M.A.1
Jeffries, H.E.2
Eisenberg, M.A.3
Harry, E.D.4
-
134
-
-
77954373218
-
Decrease in hospital-wide mortality rate after implementation of a commercially sold computerized physician order entry system
-
PID: 20439590
-
Longhurst, C. A. et al. Decrease in hospital-wide mortality rate after implementation of a commercially sold computerized physician order entry system. Pediatrics 126, 14–21 (2010)
-
(2010)
Pediatrics
, vol.126
, pp. 14-21
-
-
Longhurst, C.A.1
-
135
-
-
84878716417
-
A clinical case of electronic health record drug alert fatigue: consequences for patient outcome
-
Carspecken, C. W., Sharek, P. J., Longhurst, C. & Pageler, N. M. A clinical case of electronic health record drug alert fatigue: consequences for patient outcome. Pediatrics 131, 1970–1973 (2013)
-
(2013)
Pediatrics
, vol.131
, pp. 1970-1973
-
-
Carspecken, C.W.1
Sharek, P.J.2
Longhurst, C.3
Pageler, N.M.4
-
136
-
-
1542327773
-
Some unintended consequences of information technology in health care: the nature of patient care information system-related errors
-
PID: 14633936
-
Ash, J. S., Berg, M. & Coiera, E. Some unintended consequences of information technology in health care: the nature of patient care information system-related errors. J. Am. Med. Inform. Assoc. 11, 104–112 (2004)
-
(2004)
J. Am. Med. Inform. Assoc.
, vol.11
, pp. 104-112
-
-
Ash, J.S.1
Berg, M.2
Coiera, E.3
-
137
-
-
84946119874
-
Diagnostic accuracy of digital screening mammography with and without computer-aided detection
-
PID: 26414882
-
Lehman, C. D. et al. Diagnostic accuracy of digital screening mammography with and without computer-aided detection. JAMA Intern. Med. 175, 1828–1837 (2015)
-
(2015)
JAMA Intern. Med.
, vol.175
, pp. 1828-1837
-
-
Lehman, C.D.1
-
138
-
-
14544304095
-
Role of computerized physician order entry systems in facilitating medication errors
-
COI: 1:CAS:528:DC%2BD2MXit1WksbY%3D, PID: 15755942
-
Koppel, R. et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA 293, 1197–1203 (2005)
-
(2005)
JAMA
, vol.293
, pp. 1197-1203
-
-
Koppel, R.1
-
139
-
-
84881354155
-
Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA
-
Middleton, B. et al. Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. J. Am. Med. Inform. Assoc. 20, 2–8 (2013)
-
(2013)
J. Am. Med. Inform. Assoc.
, vol.20
, pp. 2-8
-
-
Middleton, B.1
-
140
-
-
85054640341
-
-
12 April
-
Gottlieb, S. Twitter (12 April 2018); https://twitter.com/SGottliebFDA/status/984378648781312002
-
(2018)
Twitter
-
-
Gottlieb, S.1
-
141
-
-
85054637036
-
-
Digital Health Software Precertification (Pre-Cert) Program (FDA); https://www.fda.gov/MedicalDevices/DigitalHealth/DigitalHealthPreCertProgram/default.htm
-
-
-
-
142
-
-
78149290264
-
Open mHealth architecture: an engine for health care innovation
-
COI: 1:CAS:528:DC%2BC3cXhsVClu7bE, PID: 21051617
-
Estrin, D. & Sim, I. Open mHealth architecture: an engine for health care innovation. Science 330, 759–760 (2010)
-
(2010)
Science
, vol.330
, pp. 759-760
-
-
Estrin, D.1
Sim, I.2
-
143
-
-
0023181523
-
Computer programs to support clinical decision making
-
COI: 1:STN:280:DyaL2s3is1KnsA%3D%3D, PID: 3586293
-
Shortliffe, E. H. Computer programs to support clinical decision making. JAMA 258, 61–66 (1987)
-
(1987)
JAMA
, vol.258
, pp. 61-66
-
-
Shortliffe, E.H.1
-
144
-
-
84939228529
-
Clinical chemistry laboratory automation in the 21st century—amat victoria curam (Victory loves careful preparation)
-
Armbruster, D. A., Overcash, D. R. & Reyes, J. Clinical chemistry laboratory automation in the 21st century—amat victoria curam (victory loves careful preparation). Clin. Biochem. Rev. 35, 143–153 (2014)
-
(2014)
Clin. Biochem. Rev
, vol.35
, pp. 143-153
-
-
Armbruster, D.A.1
Overcash, D.R.2
Reyes, J.3
-
145
-
-
0034293025
-
A golden age of clinical chemistry: 1948–1960
-
COI: 1:CAS:528:DC%2BD3cXnsFOhurY%3D, PID: 11017957
-
Rosenfeld, L. A golden age of clinical chemistry: 1948–1960. Clin. Chem. 46, 1705–1714 (2000)
-
(2000)
Clin. Chem.
, vol.46
, pp. 1705-1714
-
-
Rosenfeld, L.1
-
146
-
-
33845439066
-
Medication-related clinical decision support in computerized provider order entry systems: a review
-
PID: 17068355
-
Kuperman, G. J. et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J. Am. Med. Inform. Assoc. 14, 29–40 (2007)
-
(2007)
J. Am. Med. Inform. Assoc.
, vol.14
, pp. 29-40
-
-
Kuperman, G.J.1
-
147
-
-
0036884965
-
Improving recognition of drug interactions: benefits and barriers to using automated drug alerts
-
PID: 12458299
-
Glassman, P. A., Simon, B., Belperio, P. & Lanto, A. Improving recognition of drug interactions: benefits and barriers to using automated drug alerts. Med. Care 40, 1161–1171 (2002)
-
(2002)
Med. Care
, vol.40
, pp. 1161-1171
-
-
Glassman, P.A.1
Simon, B.2
Belperio, P.3
Lanto, A.4
-
149
-
-
85054158054
-
Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists
-
COI: 1:STN:280:DC%2BC1MbhslCjtA%3D%3D, PID: 29846502
-
Haenssle, H. A. et al. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists. Ann. Oncol. 29, 1836–1842 (2018)
-
(2018)
Ann. Oncol.
, vol.29
, pp. 1836-1842
-
-
Haenssle, H.A.1
|