The use of artificial neural networks to predict delayed discharge and readmission in enhanced recovery following laparoscopic colorectal cancer surgery

Techniques in Coloproctology

Volumn 19, Issue 7, 2015, Pages 419-428

  Francis, N K ^a,b   Luther, A ^a   Salib, E ^c   Allanby, L ^a   Messenger, D ^a   Allison, A S ^a   Smart, N J ^d   Ockrim, J B ^a  

^a YEOVIL DISTRICT HOSPITAL   (United Kingdom)

^b UNIVERSITY OF BRISTOL   (United Kingdom)

^c YEOVIL DISTRICT HOSPITAL NHS FOUNDATION TRUST   (United Kingdom)

^d ROYAL DEVON AND EXETER HOSPITAL   (United Kingdom)

Author keywords

Artificial neural network; Colorectal cancer surgery; ERAS

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER ADJUVANT THERAPY; CANCER PATIENT; COLORECTAL CANCER; DATA ANALYSIS; ENHANCED RECOVERY AFTER SURGERY; HOSPITAL DISCHARGE; HOSPITAL READMISSION; HUMAN; LAPAROSCOPIC SURGERY; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; OUTCOME ASSESSMENT; PERCEPTRON; PERIOPERATIVE PERIOD; PREDICTION; PROTOCOL COMPLIANCE; ADVERSE EFFECTS; AFTERCARE; AREA UNDER THE CURVE; COLON RESECTION; COLORECTAL NEOPLASMS; EVALUATION STUDY; FEMALE; LAPAROSCOPY; LENGTH OF STAY; MALE; NEOADJUVANT THERAPY; PATIENT COMPLIANCE; PROCEDURES; PROSPECTIVE STUDY; REHABILITATION; RETROSPECTIVE STUDY; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TIME FACTOR; UTILIZATION;

AFTERCARE; AREA UNDER CURVE; COLECTOMY; COLORECTAL NEOPLASMS; FEMALE; HUMANS; LAPAROSCOPY; LENGTH OF STAY; LOGISTIC MODELS; MALE; NEOADJUVANT THERAPY; NEURAL NETWORKS (COMPUTER); PATIENT COMPLIANCE; PATIENT DISCHARGE; PATIENT READMISSION; PROSPECTIVE STUDIES; RETROSPECTIVE STUDIES; TIME FACTORS;

EID: 84934442563     PISSN: 11236337     EISSN: 1128045X     Source Type: Journal    
DOI: 10.1007/s10151-015-1319-0     Document Type: Article

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