Machine learning for survival analysis: A case study on recurrence of prostate cancer

Artificial Intelligence in Medicine

Volumn 20, Issue 1, 2000, Pages 59-75

  Zupan, Blaž ^a,b,c   Demšar, Janez ^a   Kattan, Michael W ^d   Beck, J Robert ^c   Bratko, I ^a,b  

^a UNIVERSITY OF LJUBLJANA   (Slovenia)

^b JO EF STEFAN INSTITUTE   (Slovenia)

^c BAYLOR COLLEGE OF MEDICINE   (United States)

^d MEMORIAL SLOAN KETTERING CANCER CENTER   (United States)

Author keywords

Censored data; Data weighting; Machine learning; Outcome prediction after radical prostatectomy; Prognostic models in medicine; Prostate cancer recurrence; Survival analysis

Indexed keywords

DATA STRUCTURES; HOSPITAL DATA PROCESSING; LEARNING SYSTEMS; MATHEMATICAL MODELS; ONCOLOGY; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS;

CENSORED DATA; DATA WEIGHTING; PROGNOSTIC MODEL; PROSTATE CANCER RECURRENCE; RADICAL PROSTATECTOMY; SURVIVAL ANALYSIS;

MEDICAL COMPUTING;

ARTICLE; ARTIFICIAL INTELLIGENCE; CANCER RECURRENCE; CLASSIFICATION; CONTROLLED STUDY; DECISION MAKING; FOLLOW UP; HUMAN; INFORMATION PROCESSING; MACHINE; MAJOR CLINICAL STUDY; MALE; MODEL; OUTCOMES RESEARCH; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROSTATE CANCER; PROSTATECTOMY; SURVIVAL;

ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER SIMULATION; DECISION TREES; HUMANS; MALE; PROBABILITY; PROGNOSIS; PROSTATIC NEOPLASMS; RECURRENCE; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SURVIVAL ANALYSIS;

EID: 0343081009     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0933-3657(00)00053-1     Document Type: Article

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