Use of artificial neural networks to predict biological outcomes for patients receiving radical radiotherapy of the prostate

Radiotherapy and Oncology

Volumn 71, Issue 1, 2004, Pages 3-12

  Gulliford, Sarah L ^a,d   Webb, Steve ^a   Rowbottom, Carl G ^b   Corne, David W ^c   Dearnaley, David P ^a  

^a INSTITUTE OF CANCER RESEARCH   (United Kingdom)

^b CHRISTIE HOSPITAL   (United Kingdom)

^c UNIVERSITY OF EXETER   (United Kingdom)

^d IPSWICH HOSPITAL   (United Kingdom)

Author keywords

Artificial neural networks; Normal tissue complication probability; Prostate; Radiotherapy; Tumour control probability

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; BLADDER DISEASE; CANCER CONTROL; CANCER PATIENT; CANCER RADIOTHERAPY; CONTROLLED STUDY; CORRELATION ANALYSIS; DATA ANALYSIS; DOSE CALCULATION; HISTOGRAM; HUMAN; MAJOR CLINICAL STUDY; MALE; MODEL; OUTCOMES RESEARCH; PARAMETER; PREDICTION; PRESCRIPTION; PRIORITY JOURNAL; PROBABILITY; PROSTATE CANCER; RADIATION DOSE; RADIATION DOSE DISTRIBUTION; RADIOBIOLOGY; RECTUM DISEASE; RETROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY; TISSUE; TREATMENT OUTCOME; TREATMENT PLANNING;

GASTROINTESTINAL HEMORRHAGE; HUMANS; MALE; NEURAL NETWORKS (COMPUTER); PROSTATE-SPECIFIC ANTIGEN; PROSTATIC NEOPLASMS; RADIOTHERAPY, CONFORMAL; RECTAL DISEASES; RECTUM; TREATMENT OUTCOME; URINARY BLADDER; URINATION DISORDERS;

EID: 1842527859     PISSN: 01678140     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.radonc.2003.03.001     Document Type: Article

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