Missing data imputation using statistical and machine learning methods in a real breast cancer problem

Artificial Intelligence in Medicine

Volumn 50, Issue 2, 2010, Pages 105-115

  Jerez, José M ^a   Molina, Ignacio ^a   García Laencina, Pedro J ^b   Alba, Emilio ^c   Ribelles, Nuria ^c   Martín, Miguel ^d   Franco, Leonardo ^a  

^a UNIVERSITY OF MÁLAGA   (Spain)

^b TECHNICAL UNIVERSITY OF CARTAGENA   (Spain)

^c HOSPITAL UNIVERSITARIO VIRGEN DE LA VICTORIA   (Spain)

^d HOSPITAL CLÍNICO SAN CARLOS   (Spain)

Author keywords

Breast cancer prognosis; Early breast cancer; Machine learning imputation methods; Missing data; Statistical imputation techniques; Survival analysis

Indexed keywords

BREAST CANCER; EARLY BREAST CANCER; IMPUTATION TECHNIQUES; MACHINE-LEARNING; MISSING DATA; SURVIVAL ANALYSIS;

BIOINFORMATICS; LEARNING SYSTEMS; NEURAL NETWORKS; STATISTICS;

LEARNING ALGORITHMS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BREAST CANCER; CANCER RECURRENCE; CANCER RELAPSE; CANCER SURVIVAL; DEMOGRAPHY; FEMALE; HUMAN; LEARNING ALGORITHM; MACHINE LEARNING; MEDICAL INFORMATION; OUTCOME ASSESSMENT; PRIORITY JOURNAL; PROGNOSIS; RECEIVER OPERATING CHARACTERISTIC;

ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BREAST NEOPLASMS; DATABASES, FACTUAL; DEMOGRAPHY; FEMALE; HUMANS; MIDDLE AGED; MODELS, STATISTICAL; NEOPLASM RECURRENCE, LOCAL; PROGNOSIS; ROC CURVE; SURVIVAL ANALYSIS;

EID: 77957130052     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2010.05.002     Document Type: Article

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