Medicine and health care as a data problem: Will computers become better medical doctors?

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8700, Issue , 2015, Pages 21-39

  Duerr Specht, Michael ^a   Goebel, Randy ^b   Holzinger, Andreas ^c  

^a DUKE UNIVERSITY HOSPITAL   (United States)

^b UNIVERSITY OF ALBERTA   (Canada)

^c MEDICAL UNIVERSITY OF GRAZ   (Austria)

Author keywords

Big data; Data centric medicine; Medical decision support; Medical informatics; Medical reasoning; Smart health

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLUSTERING ALGORITHMS; COMPUTER GAMES; DECISION MAKING; DECISION SUPPORT SYSTEMS; HEALTH CARE; HEURISTIC METHODS; INFORMATION SCIENCE; MEDICAL COMPUTING; MEDICINE; POPULATION STATISTICS;

DATA AND INFORMATION; DATA CENTRIC; HIGH DIMENSIONAL DATA; MACHINE INTELLIGENCE; MEDICAL DECISION MAKING; MEDICAL DECISION SUPPORTS; MEDICAL INFORMATICS; MEDICAL REASONINGS;

BIG DATA;

EID: 84924349381     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-16226-3_2     Document Type: Article

References (80)

1. Moore, G.E.: Cramming more components onto integrated circuits. Electronics 38(8), 114–117 (1965)
2. Cavin, R., Lugli, P., Zhirnov, V.: Science and engineering beyond Moore’s Law. IEEE Proc. 100(13), 1720–1749 (2012)
3. Holzinger, A., Röcker, C., Ziefle, M.: From smart health to smart hospitals. In: Holzinger, A., Röcker, C., Ziefle, M. (eds.) Smart Health. LNCS, vol. 8700, pp. 1–19. Springer, Heidelberg (2015)
4. Holzinger, A., Dehmer, M., Jurisica, I.: Knowledge discovery and interactive data mining in bioinformatics - state-of-the-art, future challenges and research directions. BMC Bioinform. 15(S6), I1 (2014)
5. Alper, B.S., Hand, J.A., Elliott, S.G., Kinkade, S., Hauan, M.J., Onion, D.K., Sklar, B.M.: How much effort is needed to keep up with the literature relevant for primary care? J. Med. Lib. Assoc. 92(4), 429–437 (2004)
6. Kohn, L.T., Corrigan, J., Donaldson, M.S.: To err is human: building a safer health system. National Academy Press, Washington (DC) (2000)
7. Patel, V.L., Kahol, K., Buchman, T.: Biomedical complexity and error. J. Biomed. Inform. 44(3), 387–389 (2011)
8. Poole, D.: Explanation and prediction: an architecture for default and abductive reasoning. Comput. Intell. 5(2), 97–110 (1989)
9. Dong-Hee, S., Min Jae, C.: Ecological views of big data: Perspectives and issues. Telematics Inform. 32(2), 311–320 (2015)
10. Holzinger, A.: Biomedical Informatics: Discovering Knowledge in Big Data. Springer, New York (2014)
11. Johnson-Laird, P.N.: Deductive reasoning. Ann. Rev. Psychol. 50, 109–135 (1999)
12. Ferrucci, D., Brown, E., Chu-Carroll, J., Fan, J., Gondek, D., Kalyanpur, A.A., Lally, A., Murdock, J.W., Nyberg, E., Prager, J.: Building Watson: An overview of the DeepQA project. AI Mag. 31(3), 59–79 (2010)
13. Sackett, D.L., Rosenberg, W.M., Gray, J., Haynes, R.B., Richardson, W.S.: Evidence based medicine: what it is and what it isn’t. BMJ. Br. Med. J. 312(7023), 71 (1996)
14. Guyatt, G.: Evidence based medicine - a new approach to teaching the practice of medicine. JAMA-J. Am. Med. Assoc. 268(17), 2420–2425 (1992)
15. Holzinger, A.: Trends in interactive knowledge discovery for personalized medicine: cognitive science meets machine learning. Intell. Inf. Bull. 15(1), 6–14 (2014)
16. Holzinger, A.: Lecture 8 biomedical decision making: reasoning and decision support. In: Biomedical Informatics, pp. 345–377. Springer (2014)
17. Ferrucci, D., Levas, A., Bagchi, S., Gondek, D., Mueller, E.T.: Watson: Beyond jeopardy! Artif. Intell. 199–200, 93–105 (2013)
18. Holzinger, A., Stocker, C., Ofner, B., Prohaska, G., Brabenetz, A., Hofmann-Wellenhof, R.: Combining HCI, natural language processing, and knowledge discovery - potential of IBM content analytics as an assistive technology in the biomedical field. In: Holzinger, A., Pasi, G. (eds.) HCI-KDD 2013. LNCS, vol. 7947, pp. 13–24. Springer, Heidelberg (2013)
19. Ferrucci, D.A.: Introduction to “This is Watson”. IBM J. Res. Develop. 56, 3–4 (2012)
20. Gondek, D.C., Lally, A., Kalyanpur, A., Murdock, J.W., Duboue, P.A., Zhang, L., Pan, Y., Qiu, Z.M., Welty, C.: A framework for merging and ranking of answers in DeepQA. IBM J. Res. Develop. 56, 3–4 (2012)
21. Epstein, E.A., Schor, M.I., Iyer, B.S., Lally, A., Brown, E.W., Cwiklik, J.: Making Watson fast. IBM J. Res. Develop. 56, 3–4 (2012)
22. Lewis, B.L.: In the game: The interface between Watson and Jeopardy! IBM Journal of Research and Development 56(3–4), (2012)
23. Newborn, M.: Deep Blue’s contribution to AI. Ann. Math. Artif. Intell. 28(1–4), 27–30 (2000)
24. Campbell, M., Hoane, A.J., Hsu, F-h: Deep blue. Artif. Intell. 134(1), 57–83 (2002)
25. Newell, A., Shaw, J.C., Simon, H.A.: Chess-playing programs and the problem of complexity. IBM J. Res. Dev. 2(4), 320–335 (1958)
26. Ensmenger, N.: Is chess the drosophila of artificial intelligence? A social history of an algorithm. Soc. Stud. Sci. 42(1), 5–30 (2012)
27. Navigli, R., Velardi, P.: Structural semantic interconnections: A knowledge-based approach to word sense disambiguation. IEEE Trans. Pattern Anal. Mach. Intell. 27(7), 1075–1086 (2005)
28. Bhala, R.V.V., Abirami, S.: Trends in word sense disambiguation. Artif. Intell. Rev. 42(2), 159–171 (2014)
29. Tesauro, G., Gondek, D.C., Lenchner, J., Fan, J., Prager, J.M.: Simulation, learning, and optimization techniques in Watson’s game strategies. IBM J. Res. Develop. 56, 3–4 (2012)
30. Tesauro, G., Gondek, D.C., Lenchner, J., Fan, J., Prager, J.M.: Analysis of WATSON’s strategies for playing jeopardy! J. Artif. Intell. Res. 47, 205–251 (2013)
31. Simon, H.A.: Studying human intelligence by creating artificial intelligence. Am. Sci. 69(3), 300–309 (1981)
32. Turing, A.M.: Computing machinery and intelligence. Mind 59(236), 433–460 (1950)
33. Detterman, D.K.: A challenge to Watson. Intelligence 39(2–3), 77–78 (2011)
34. Rachlin, H.: Making IBM’s computer, watson, human. Behav. Anal. 35(1), 1–16 (2012)
35. Sun, Z.H., Finnie, G., Weber, K.: Abductive case-based reasoning. Int. J. Intell. Syst. 20(9), 957–983 (2005)
36. Holzinger, A., Jurisica, I.: Knowledge discovery and data mining in biomedical informatics: the future is in integrative, interactive machine learning solutions. In: Holzinger, A., Jurisica, I. (eds.) Interactive Knowledge Discovery and Data Mining in Biomedical Informatics. LNCS, vol. 8401, pp. 1–18. Springer, Heidelberg (2014)
37. Chip. http://business.chip.de/news/IBM-Watson-Sein-erster-Job-ist-Arzthelfer_51623616.html
38. Holzinger, A.: Human-computer interaction and knowledge discovery (HCI-KDD): What is the benefit of bringing those two fields to work together? In: Cuzzocrea, A., Kittl, C., Simos, D.E., Weippl, E., Xu, L. (eds.) CD-ARES 2013. LNCS, vol. 8127, pp. 319–328. Springer, Heidelberg (2013)
39. Nadkarni, P.M., Ohno-Machado, L., Chapman, W.W.: Natural language processing: an introduction. J. Am. Med. Inform. Assoc. 18(5), 544–551 (2011)
40. Murdock, J.W., Fan, J., Lally, A., Shima, H., Boguraev, B.K.: Textual evidence gathering and analysis. IBM J. Res. Dev. 56(3–4), 1–14 (2012)
41. Röntgen, W.C.: On a new kind of rays. Science 3(59), 227–231 (1896)
42. Robert Wood Johnson Foundation (RWJF). http://www.rwjf.org/en/about-rwjf/newsroom/ newsroom-content/2013/07/hospitals–physicians-make-major-strides-in-electronic-healthre.html
43. Miller, R.A.: Medical diagnostic decision support systems - past, present and future. J. Am. Med. Inform. Assoc. 1(1), 8–27 (1994)
44. Techcruch. http://techcrunch.com/2012/01/10/doctors-or-algorithms/
45. Boisot, M., Canals, A.: Data, information and knowledge: have we got it right? J. Evol. Econ. 14(1), 43–67 (2004)
46. Wickens, C.D.: Engineering Psychology and Human Performance. Charles Merrill, Columbus (1984)
47. Holzinger, A., Stocker, C., Dehmer, M.: Big complex biomedical data: towards a taxonomy of data. In: Obaidat, M.S., Filipe, J. (eds.) Communications in Computer and Information Science CCIS 455, pp. 3–18. Springer, Berlin Heidelberg (2014)
48. Holzinger, A.: On knowledge discovery and interactive intelligent visualization of biomedical data: Challenges in human–computer interaction & biomedical informatics. In: Helferd, M., Fancalanci, C., Filipe, J. (eds.) DATA - International Conference on Data Technologies and Applications, pp. 5–16. INSTICC, Rome (2012)
49. Marinescu, D.C.: Classical and Quantum Information. Academic Press, Burlington (2011)
50. von Neumann, J.: Electronic methods of computation. Bull. Am. Acad. Arts Sci. 1(3), 2–4 (1948)
51. Adelson, E.H.: Checkershadow illusion. http://web.mit.edu/persci/people/adelson/checker shadow_illusion.html (last Accessed 24 November 2014) (1995)
52. Geisler, W.S., Kersten, D.: Illusions, perception and Bayes. Nat. Neurosci. 5(6), 508–510 (2002)
53. von Ahn, L., Blum, M., Hopper, N.J., Langford, J.: CAPTCHA: Using hard AI problems for security. In: Biham, E. (ed.) EUROCRYPT 2003. LNCS, vol. 2656. Springer, Heidelberg (2003)
54. Rusu, A., Govindaraju, V., Soc, I.C.: Handwritten CAPTCHA: Using the difference in the abilities of humans and machines in reading handwritten words. IEEE Computer Society, Los Alamitos (2004)
55. Belk, M., Germanakos, P., Fidas, C., Holzinger, A., Samaras, G.: Towards the personalization of CAPTCHA mechanisms based on individual differences in cognitive processing. In: Holzinger, A., Ziefle, M., Hitz, M., Debevc, M. (eds.) SouthCHI 2013. LNCS, vol. 7946, pp. 409–426. Springer, Heidelberg (2013)
56. Weiss, Y., Simoncelli, E.P., Adelson, E.H.: Motion illusions as optimal percepts. Nat. Neurosci. 5(6), 598–604 (2002)
57. Leunens, G., Verstraete, J., Vandenbogaert, W., Vandam, J., Dutreix, A., Vanderschueren, E.: Human errors in data transfer during the preparation and delivery of radiation treatment affecting the final reasult - garbage in, garbage out. Radiother. Oncol. 23(4), 217–222 (1992)
58. Kahneman, D.: Remarks on attention control. Acta Psychologica 33, 118–131 (1970)
59. Shiffrin, R.M., Gardner, G.T.: Visual processing capacity and attention control. J. Exp. Psychol. 93(1), 72 (1972)
60. Duncan, J.: Selective attention and the organization of visual information. J. Exp. Psychol. Gen. 113(4), 501–517 (1984)
61. Anderson, C.H., Van Essen, D.C., Olshausen, B.A.: Directed visual attention and the dynamic control of information flow. In: Itti, L., Rees, G., Tsotsos, J.K. (eds.) Neurobiology of Attention, pp. 11–17. Academic Press/Elservier, Burlington (2005)
62. Patel, V.L., Arocha, J.F., Zhang, J.: Thinking and reasoning in medicine. Cambridge Handb. Think. Reason. 14, 727–750 (2005)
63. Alfaro-LeFevre, R.: Critical Thinking, Clinical Reasoning, and Clinical Judgment: A Practical Approach. Elsevier Saunders, Philadelphia (2013)
64. Rice, S.P., Boregowda, K., Williams, M.T., Morris, G.C., Okosieme, O.E.: A Welsh-sparing dysphasia. Lancet 382(9904), 1608 (2013)
65. Croskerry, P.: The importance of cognitive errors in diagnosis and strategies to minimize them. Acad. Med. 78(8), 775–780 (2003)
66. Berner, E.S., Graber, M.L.: Overconfidence as a cause of diagnostic error in medicine. Am. J. Med. 121(5), S2–S23 (2008)
67. Shortliffe, E.H., Buchanan, B.G.: A model of inexact reasoning in medicine. Math. Biosci. 23(3), 351–379 (1975)
68. Shortliffe, E.H., Buchanan, B.G.: Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Addison-Wesley, Reading (1984)
69. Washington Technology. http://washingtontechnology.com/articles/2011/02/17/ibmwatson-next-steps.aspx
70. Stocker, C., Marzi, L.-M., Matula, C., Schantl, J., Prohaska, G., Brabenetz, A., Holzinger, A.: Enhancing patient safety through human-computer information retrieval on the example of german-speaking surgical reports. In: TIR 2014 - 11th International Workshop on Textbased Information Retrieval, pp. 1–5. IEEE (2014)
71. Simpson, E.H.: The interpretation of interaction in contingency tables. J. R. Stat. Soc. Ser. B-Stat. Methodol. 13(2), 238–241 (1951)
72. Croskerry, P., Nimmo, G.: Better clinical decision making and reducing diagnostic error. J. R. Coll. Physicians Edinb. 41(2), 155–162 (2011)
73. Djulbegovic, B., Hozo, I., Beckstead, J., Tsalatsanis, A., Pauker, S.: Dual processing model of medical decision-making. BMC Med. Inform. Decis. Mak. 12(1), 94 (2012)
74. Huppertz, B., Holzinger, A.: Biobanks–A source of large biological data sets: open problems and future challenges. In: Holzinger, A., Jurisica, I. (eds.) Interactive Knowledge Discovery and Data Mining in Biomedical Informatics. LNCS, vol. 8401, pp. 317–330. Springer, Heidelberg (2014)
75. Downing, G., Boyle, S., Brinner, K., Osheroff, J.: Information management to enable personalized medicine: stakeholder roles in building clinical decision support. BMC Med. Inform. Decis. Mak. 9(1), 1–11 (2009)
76. Rosenbloom, S.T., Denny, J.C., Xu, H., Lorenzi, N., Stead, W.W., Johnson, K.B.: Data from clinical notes: a perspective on the tension between structure and flexible documentation. J. Am. Med. Inf. Assoc. 18(2), 181–186 (2011)
77. Lenfant, C.: Clinical research to clinical practice — lost in translation? N. Engl. J. Med. 349(9), 868–874 (2003)
78. Love, J.S., Wright, A., Simon, S.R., Jenter, C.A., Soran, C.S., Volk, L.A., Bates, D.W., Poon, E.G.: Are physicians’ perceptions of healthcare quality and practice satisfaction affected by errors associated with electronic health record use? J. Am. Med. Inf. Assoc. 19(4), 610–614 (2011)
79. Bowman, S.: Impact of electronic health record systems on information integrity: quality and safety implications. Perspect. Health Inf. Manage. 10, 1–19 (2013)
80. Morris, Z.S., Wooding, S., Grant, J.: The answer is 17 years, what is the question: understanding time lags in translational research. J. R. Soc. Med. 104(12), 510–520 (2011)