Literature DB >> 22878787

Artificial neural network model for predicting 5-year mortality after surgery for hepatocellular carcinoma: a nationwide study.

Hon-Yi Shi1, King-Teh Lee, Jhi-Joung Wang, Ding-Ping Sun, Hao-Hsien Lee, Chong-Chi Chiu.   

Abstract

BACKGROUND: To validate the use of artificial neural network (ANN) models for predicting 5-year mortality in HCC and to compare their predictive capability with that of logistic regression (LR) models.
METHODS: This study retrospectively compared LR and ANN models based on initial clinical data for 22,926 HCC surgery patients from 1998 to 2009. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and to rank the importance of variables.
RESULTS: Compared to the LR models, the ANN models had a better accuracy rate in 96.57 % of cases, a better Hosmer-Lemeshow statistic in 0.34 of cases, and a better receiver operating characteristic curves in 88.51 % of cases. Surgeon volume was the most influential (sensitive) parameter affecting 5-year mortality followed by hospital volume and Charlson co-morbidity index.
CONCLUSIONS: In comparison with the conventional LR model, the ANN model in this study was more accurate in predicting 5-year mortality. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data.

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Year:  2012        PMID: 22878787     DOI: 10.1007/s11605-012-1986-3

Source DB:  PubMed          Journal:  J Gastrointest Surg        ISSN: 1091-255X            Impact factor:   3.452


  18 in total

1.  Surgical outcomes for hepatocellular carcinoma in nonalcoholic fatty liver disease.

Authors:  Toshifumi Wakai; Yoshio Shirai; Jun Sakata; Pavel Vladimirovich Korita; Yoichi Ajioka; Katsuyoshi Hatakeyama
Journal:  J Gastrointest Surg       Date:  2011-04-22       Impact factor: 3.452

2.  Procedure volume as a predictor of surgical outcomes.

Authors:  Edward H Livingston; Jing Cao
Journal:  JAMA       Date:  2010-07-07       Impact factor: 56.272

3.  Adequate extent in radical re-resection of incidental gallbladder carcinoma: analysis of the German Registry.

Authors:  Thorsten Oliver Goetze; Vittorio Paolucci
Journal:  Surg Endosc       Date:  2010-02-23       Impact factor: 4.584

Review 4.  Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes.

Authors:  J V Tu
Journal:  J Clin Epidemiol       Date:  1996-11       Impact factor: 6.437

5.  A population-based study of hepatitis D virus as potential risk factor for hepatocellular carcinoma.

Authors:  Jianguang Ji; Kristina Sundquist; Jan Sundquist
Journal:  J Natl Cancer Inst       Date:  2012-03-14       Impact factor: 13.506

6.  Risk adjustment in outcome assessment: the Charlson comorbidity index.

Authors:  W D'Hoore; C Sicotte; C Tilquin
Journal:  Methods Inf Med       Date:  1993-11       Impact factor: 2.176

7.  Clinicopathological determinants of survival after hepatic resection of hepatocellular carcinoma in 97 patients--experience from an Australian hepatobiliary unit.

Authors:  Terence C Chua; Akshat Saxena; Francis Chu; Winston Liauw; Jing Zhao; David L Morris
Journal:  J Gastrointest Surg       Date:  2010-06-29       Impact factor: 3.452

8.  Preoperative prediction of hepatocellular carcinoma tumour grade and micro-vascular invasion by means of artificial neural network: a pilot study.

Authors:  Alessandro Cucchetti; Fabio Piscaglia; Antonia D'Errico Grigioni; Matteo Ravaioli; Matteo Cescon; Matteo Zanello; Gian Luca Grazi; Rita Golfieri; Walter Franco Grigioni; Antonio Daniele Pinna
Journal:  J Hepatol       Date:  2010-03-24       Impact factor: 25.083

9.  Prognostic factors and 10-year survival in patients with hepatocellular carcinoma after curative hepatectomy.

Authors:  Sung Hoon Kim; Sae Byeol Choi; Jae Gil Lee; Seung Up Kim; Mi-Suk Park; Do Young Kim; Jin Sub Choi; Kyung Sik Kim
Journal:  J Gastrointest Surg       Date:  2011-02-19       Impact factor: 3.452

10.  Prediction of asymptomatic cirrhosis in chronic hepatitis C patients: accuracy of artificial neural networks compared with logistic regression models.

Authors:  Massimo Cazzaniga; Francesco Salerno; Gianmario Borroni; Roberto Ceriani; Giulia Stucchi; Patrizia Guerzoni; Maria Antonietta Casiraghi; Maurizio Tommasini
Journal:  Eur J Gastroenterol Hepatol       Date:  2009-06       Impact factor: 2.566

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  13 in total

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

Authors:  N K Francis; A Luther; E Salib; L Allanby; D Messenger; A S Allison; N J Smart; J B Ockrim
Journal:  Tech Coloproctol       Date:  2015-06-19       Impact factor: 3.781

2.  Pre-operative prediction of surgical morbidity in children: comparison of five statistical models.

Authors:  Jennifer N Cooper; Lai Wei; Soledad A Fernandez; Peter C Minneci; Katherine J Deans
Journal:  Comput Biol Med       Date:  2014-12-08       Impact factor: 4.589

3.  Machine Learning Algorithms for understanding the determinants of under-five Mortality.

Authors:  Rakesh Kumar Saroj; Pawan Kumar Yadav; Rajneesh Singh; Obvious N Chilyabanyama
Journal:  BioData Min       Date:  2022-09-24       Impact factor: 4.079

4.  Volume-outcome associations after major hepatectomy for hepatocellular carcinoma: a nationwide Taiwan study.

Authors:  Chih-Cheng Lu; Chong-Chi Chiu; Jhi-Joung Wang; Yu-Hsien Chiu; Hon-Yi Shi
Journal:  J Gastrointest Surg       Date:  2014-04-15       Impact factor: 3.452

5.  Predicting outcomes in patients with perforated gastroduodenal ulcers: artificial neural network modelling indicates a highly complex disease.

Authors:  K Søreide; K Thorsen; J A Søreide
Journal:  Eur J Trauma Emerg Surg       Date:  2014-06-14       Impact factor: 3.693

6.  Artificial Neural Network Individualised Prediction of Time to Colorectal Cancer Surgery.

Authors:  N J Curtis; G Dennison; E Salib; D A Hashimoto; N K Francis
Journal:  Gastroenterol Res Pract       Date:  2019-07-09       Impact factor: 2.260

7.  Prognostic role of artificial intelligence among patients with hepatocellular cancer: A systematic review.

Authors:  Quirino Lai; Gabriele Spoletini; Gianluca Mennini; Zoe Larghi Laureiro; Diamantis I Tsilimigras; Timothy Michael Pawlik; Massimo Rossi
Journal:  World J Gastroenterol       Date:  2020-11-14       Impact factor: 5.742

8.  Development of machine learning-based clinical decision support system for hepatocellular carcinoma.

Authors:  Gwang Hyeon Choi; Jihye Yun; Jonggi Choi; Danbi Lee; Ju Hyun Shim; Han Chu Lee; Young-Hwa Chung; Yung Sang Lee; Beomhee Park; Namkug Kim; Kang Mo Kim
Journal:  Sci Rep       Date:  2020-09-09       Impact factor: 4.379

9.  Modern perioperative medicine - past, present, and future.

Authors:  Harry F Dean; Fiona Carter; Nader K Francis
Journal:  Innov Surg Sci       Date:  2019-12-05

10.  A scoring system based on artificial neural network for predicting 10-year survival in stage II A colon cancer patients after radical surgery.

Authors:  Jian-Hong Peng; Yu-Jing Fang; Cai-Xia Li; Qing-Jian Ou; Wu Jiang; Shi-Xun Lu; Zhen-Hai Lu; Pei-Xing Li; Jing-Ping Yun; Rong-Xin Zhang; Zhi-Zhong Pan; De Sen Wan
Journal:  Oncotarget       Date:  2016-04-19
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