메뉴 건너뛰기




Volumn 4, Issue 1, 2007, Pages 39-45

Technology Insight: Will systems pathology replace the pathologist?

Author keywords

Pathology automation; Predictive medicine; Prostate cancer; Systems pathology

Indexed keywords

PROSTATE SPECIFIC ANTIGEN;

EID: 33846049942     PISSN: 17434270     EISSN: 17434289     Source Type: Journal    
DOI: 10.1038/ncpuro0669     Document Type: Review
Times cited : (40)

References (20)
  • 1
    • 0032537993 scopus 로고    scopus 로고
    • Competing risk analysis of men aged 55 to 74 years at diagnosis managed conservatively for clinically localized prostate cancer
    • Albertsen PC et al. (1998) Competing risk analysis of men aged 55 to 74 years at diagnosis managed conservatively for clinically localized prostate cancer. JAMA 280: 975-980
    • (1998) JAMA , vol.280 , pp. 975-980
    • Albertsen, P.C.1
  • 2
    • 0041970165 scopus 로고    scopus 로고
    • Ten-year survival after radical prostatectomy: Specimen Gleason score is the predictor in organ-confined prostate cancer
    • Bianco FJ Jr et al. (2003) Ten-year survival after radical prostatectomy: Specimen Gleason score is the predictor in organ-confined prostate cancer. Clin Prostate Cancer 1: 242-247
    • (2003) Clin Prostate Cancer , vol.1 , pp. 242-247
    • Bianco Jr., F.J.1
  • 3
    • 0037815077 scopus 로고    scopus 로고
    • Correlation of minute (0.5 mm or less) focus of prostate adenocarcinoma on needle biopsy with radical prostatectomy specimen: Role of prostate specific antigen density
    • Alan RW et al. (2003) Correlation of minute (0.5 mm or less) focus of prostate adenocarcinoma on needle biopsy with radical prostatectomy specimen: Role of prostate specific antigen density. J Urol 170: 370-372
    • (2003) J Urol , vol.170 , pp. 370-372
    • Alan, R.W.1
  • 4
    • 16244376500 scopus 로고    scopus 로고
    • Molecular markers of prostate cancer outcome
    • Quinn DI et al. (2005) Molecular markers of prostate cancer outcome. European J Cancer 41: 858-887
    • (2005) European J Cancer , vol.41 , pp. 858-887
    • Quinn, D.I.1
  • 5
    • 4444356703 scopus 로고    scopus 로고
    • The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia
    • Diamond J et al. (2004) The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia. Hum Pathol 35: 1121-1131
    • (2004) Hum Pathol , vol.35 , pp. 1121-1131
    • Diamond, J.1
  • 6
    • 84948685841 scopus 로고    scopus 로고
    • A multispectral computer vision system for automatic grading of prostatic neoplasia
    • In July 7-10 2002, Washington, DC
    • Roula MA et al. (2002) A multispectral computer vision system for automatic grading of prostatic neoplasia. In Proceedings of the IEEE International Symposium on Biomedical Imaging, July 7-10 2002, Washington, DC, 193-196
    • (2002) Proceedings of the IEEE International Symposium on Biomedical Imaging , pp. 193-196
    • Roula, M.A.1
  • 7
    • 0029012972 scopus 로고
    • A hybrid neural and statistical classifier system for histopathologic grading of prostate lesions
    • Stotzka R et al. (1995) A hybrid neural and statistical classifier system for histopathologic grading of prostate lesions. Anal Quant Cytol Histol 17: 204-218
    • (1995) Anal Quant Cytol Histol , vol.17 , pp. 204-218
    • Stotzka, R.1
  • 8
    • 0032998809 scopus 로고    scopus 로고
    • Similarity measurement method for the classification of architecturally differentiated images
    • Smith Y et al. (1999) Similarity measurement method for the classification of architecturally differentiated images. Comp Biomed Res 32: 1-12
    • (1999) Comp Biomed Res , vol.32 , pp. 1-12
    • Smith, Y.1
  • 9
    • 0032680237 scopus 로고    scopus 로고
    • Evaluation of prostate tumor grades by content-based image retrieval
    • In 14 October 1998, Washington, DC, 3584: (Ed. Merickso RJ)
    • Wetzel AW et al. (1999) Evaluation of prostate tumor grades by content-based image retrieval. In 27th AIPR Workshop: Advances in Computer-Assisted Recognition, 14 October 1998, Washington, DC, 3584: 244-252 (Ed. Merickso RJ)
    • (1999) 27th AIPR Workshop: Advances in Computer-Assisted Recognition , pp. 244-252
    • Wetzel, A.W.1
  • 12
    • 0035887459 scopus 로고    scopus 로고
    • Molecular classification of human carcinomas by use of gene expression signatures
    • Su Al et al. (2001) Molecular classification of human carcinomas by use of gene expression signatures. Cancer Res 61: 7388-7393
    • (2001) Cancer Res , vol.61 , pp. 7388-7393
    • Su, Al.1
  • 13
    • 0000060617 scopus 로고    scopus 로고
    • Molecular classification of multiple tumor types
    • Yeang CH et al. (2001) Molecular classification of multiple tumor types. Bioinformatics 17 (Suppl 1): S316-S322
    • (2001) Bioinformatics , vol.17 , Issue.SUPPL. 1
    • Yeang, C.H.1
  • 15
    • 0037391756 scopus 로고    scopus 로고
    • Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning
    • Ye QH et al. (2003) Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning. Nat Med 9: 416-423
    • (2003) Nat Med , vol.9 , pp. 416-423
    • Ye, Q.H.1
  • 16
    • 0034602774 scopus 로고    scopus 로고
    • Knowledgebased analysis of microarray gene expression data using support vector machines
    • Brown MPS et al. (2000) Knowledgebased analysis of microarray gene expression data using support vector machines. Proc Natl Acad Sci USA 97: 262-267
    • (2000) Proc Natl Acad Sci USA , vol.97 , pp. 262-267
    • Brown, M.P.S.1
  • 17
    • 0031921607 scopus 로고    scopus 로고
    • Feed forward neural networks for the analysis of censored survival data: A partial logistic regression approach
    • Biganzoli E et al. (1998) Feed forward neural networks for the analysis of censored survival data: A partial logistic regression approach. Stat Med 17: 1169-1186
    • (1998) Stat Med , vol.17 , pp. 1169-1186
    • Biganzoli, E.1
  • 18
    • 0031513627 scopus 로고    scopus 로고
    • Modular neural networks for medical prognosis: Quantifying the benefits of combining neural networks for survival prediction
    • Ohno-Machado L and Musen MA. (1997) Modular neural networks for medical prognosis: Quantifying the benefits of combining neural networks for survival prediction. Connect Sci 9: 71-86
    • (1997) Connect Sci , vol.9 , pp. 71-86
    • Ohno-Machado, L.1    Musen, M.A.2
  • 19
    • 0031731379 scopus 로고    scopus 로고
    • Experiments to determine whether recursive partitioning or an artifi-cial neural network overcomes theoretical limitation of cox proportional hazards regression
    • Kattan MW et al. (1998) Experiments to determine whether recursive partitioning or an artifi-cial neural network overcomes theoretical limitation of cox proportional hazards regression. Comput Biomed Res 31: 363-373
    • (1998) Comput Biomed Res , vol.31 , pp. 363-373
    • Kattan, M.W.1
  • 20
    • 0031233464 scopus 로고    scopus 로고
    • On the use of artificial neural networks for the analysis of survival data
    • Brown SF et al. (1997) On the use of artificial neural networks for the analysis of survival data. IEEE Trans Neural Netw 8: 1071-1077
    • (1997) IEEE Trans Neural Netw , vol.8 , pp. 1071-1077
    • Brown, S.F.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.