Predicting response to neoadjuvant chemotherapy with PET imaging using convolutional neural networks

PLoS ONE

Volumn 10, Issue 9, 2015, Pages

  Ypsilantis, Petros Pavlos ^a   Siddique, Musib ^a   Sohn, Hyon Mok ^a   Davies, Andrew ^a   Cook, Gary ^a   Goh, Vicky ^a   Montana, Giovanni ^a  

^a KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

FLUORODEOXYGLUCOSE F 18;

ADULT; AGED; ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOMICS; CANCER ADJUVANT THERAPY; CLASSIFIER; CONVOLUTIONAL NEURAL NETWORK; DRUG RESPONSE; ESOPHAGUS CANCER; FEMALE; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; OVERALL SURVIVAL; POSITRON EMISSION TOMOGRAPHY; RADIOMICS; SENSITIVITY AND SPECIFICITY; TUMOR REGRESSION; DIAGNOSTIC IMAGING; ESOPHAGEAL NEOPLASMS; IMAGE PROCESSING; KAPLAN MEIER METHOD; MIDDLE AGED; NEOADJUVANT THERAPY; TREATMENT OUTCOME; VERY ELDERLY;

ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; ESOPHAGEAL NEOPLASMS; FEMALE; FLUORODEOXYGLUCOSE F18; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; KAPLAN-MEIER ESTIMATE; MALE; MIDDLE AGED; NEOADJUVANT THERAPY; NEURAL NETWORKS (COMPUTER); POSITRON-EMISSION TOMOGRAPHY; TREATMENT OUTCOME;

EID: 84944810500     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0137036     Document Type: Article

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