Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer

Annals of Surgical Oncology

Volumn 22, Issue 12, 2015, Pages 3970-3975

  Enshaei, A ^a   Robson, C N ^a   Edmondson, R J ^b  

^a NEWCASTLE UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

PACLITAXEL;

ACCURACY; ALGORITHM; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; CANCER CHEMOTHERAPY; CANCER PATIENT; CANCER PROGNOSIS; CANCER SURVIVAL; CYTOREDUCTIVE SURGERY; FEMALE; HUMAN; MAJOR CLINICAL STUDY; MULTIMODALITY CANCER THERAPY; OVARY CARCINOMA; OVERALL SURVIVAL; SURVIVAL TIME; BAYES THEOREM; COMPARATIVE STUDY; DECISION TREE; NEOPLASMS, GLANDULAR AND EPITHELIAL; OVARIAN NEOPLASMS; PREDICTIVE VALUE; PROGNOSIS; PROPORTIONAL HAZARDS MODEL; RECEIVER OPERATING CHARACTERISTIC; SUPPORT VECTOR MACHINE; SURVIVAL RATE;

ALGORITHMS; AREA UNDER CURVE; BAYES THEOREM; CYTOREDUCTION SURGICAL PROCEDURES; DECISION TREES; FEMALE; HUMANS; NEOPLASMS, GLANDULAR AND EPITHELIAL; NEURAL NETWORKS (COMPUTER); OVARIAN NEOPLASMS; PREDICTIVE VALUE OF TESTS; PROGNOSIS; PROPORTIONAL HAZARDS MODELS; ROC CURVE; SUPPORT VECTOR MACHINE; SURVIVAL RATE;

EID: 84943362394     PISSN: 10689265     EISSN: 15344681     Source Type: Journal    
DOI: 10.1245/s10434-015-4475-6     Document Type: Article

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