Comparison of artificial neural networks with logistic regression in prediction of gallbladder disease among obese patients

Digestive and Liver Disease

Volumn 39, Issue 4, 2007, Pages 356-362

  Liew, P L ^a   Lee, Y C ^b,d   Lin, Y C ^c   Lee, T S ^b   Lee, W J ^d   Wang, W ^e   Chien, C W ^f  

^a EN CHU KONG HOSPITAL   (Taiwan)

^b FU JEN CATHOLIC UNIVERSITY   (Taiwan)

^c SOOCHOW UNIVERSITY   (Taiwan)

^d MIN SHENG GENERAL HOSPITAL   (Taiwan)

^e TAIPEI MEDICAL UNIVERSITY HOSPITAL   (Taiwan)

^f NATIONAL YANG MING UNIVERSITY   (Taiwan)

Author keywords

Gallbladder disease; Logistic regression; Neural networks; Obesity

Indexed keywords

CHOLESTEROL; GLUCOSE;

ADULT; AGE; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; BARIATRIC SURGERY; BODY MASS; CHOLECYSTECTOMY; CONTROLLED STUDY; DATA MINING; DIASTOLIC BLOOD PRESSURE; DISEASE ASSOCIATION; DISEASE CLASSIFICATION; FEMALE; GALLBLADDER DISEASE; GALLSTONE; GLUCOSE METABOLISM; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; HYPERCHOLESTEROLEMIA; INFLAMMATION; LABORATORY TEST; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; MALE; MEDICAL RECORD; OBESITY; PATHOPHYSIOLOGY; PREDICTION; PREVALENCE; RISK ASSESSMENT; RISK FACTOR; SEX DIFFERENCE; TAIWAN;

ADULT; ALGORITHMS; BARIATRIC SURGERY; BLOOD PRESSURE; CHOLECYSTECTOMY; CHOLECYSTITIS; CHOLESTEROL; DIASTOLE; FEMALE; GALLBLADDER; GALLSTONES; GLUCOSE; HUMANS; LOGISTIC MODELS; MALE; NEURAL NETWORKS (COMPUTER); OBESITY; RETROSPECTIVE STUDIES; RISK FACTORS;

EID: 33947259345     PISSN: 15908658     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dld.2007.01.003     Document Type: Article

References (32)

1. Aidonopoulos A.P., Papavramidis S.T., Zaraboukas T.G., Habib H.W., and Pothoulakis I.G. Gallbladder findings after cholecystectomy in morbidly obese patients. Obes Surg 4 (1994) 8-12
2. Fobi M., Lee H., Igwe D., Felahy B., James E., Stanczyk M., et al. Prophylactic cholecystectomy with gastric bypass operation: incidence of gallbladder disease. Obes Surg 12 (2002) 350-353
3. Dittrick G.W., Thompson J.S., Campos D., Bremers D., and Sudan D. Gallbladder pathology in morbid obesity. Obes Surg 15 (2005) 238-242
4. Lee W.J., and Wang W. Bariatric surgery: Asia-Pacific perspective. Obes Surg 15 (2005) 751-757
5. Lu S.N., Chang W.Y., Wang L.Y., Hsieh M.Y., Chuang W.L., Chen S.C., et al. Risk factors for gallstones among Chinese in Taiwan. J Clin Gastroenterol 12 (1990) 542-546
6. Curt H. The devil's in the detail techniques: tools, and applications for database mining and knowledge discovery-Part. Intell Software Strategies (1995) 1-15
7. Pass S. Discovering value in a mountain of data. OR/MS Today (1997) 24-28
8. Chen M.S., Han J., and Yu P.S. Data mining: an overview from a database perspective. IEEE Trans Knowledge Data Eng 8 (1996) 866-883
9. Fayyad U., Gregory P.S., and Smyth P. The KDD process for extracting useful knowledge from volumes of data. Commun ACM 39 (1996) 27-34
10. Cabena P., Hadjinian P., Stadler R., Verhees J., and Zanasi A. Discovering data mining from concept to implementation (1998), Prentice-Hall, NJ, Upper Saddle River
11. Lee G., Sung T.K., and Chang N. Dynamics of modeling in data mining: interpretive approach to bankruptcy prediction. J Manage Inf Syst 16 (1999) 63-85
12. Ngan P.S., Wong M.L., Lam W., Leung K.S., and Cheng J.C.Y. Medical data mining using evolutionary computation. Artif Intell Med 16 (1999) 73-96
13. Pendharkar P.C., Rodger J.A., Yaverbaum G.J., Herman N., and Benner M. Associations statistical, mathematical and neural approaches for mining breast cancer patterns. Expert Syst Appl 17 (1999) 223-232
14. Chou S.M., Lee T.S., Shao Y.E., and Chen I.F. Mining the breast cancer pattern using artificial neural networks and multivariate adaptive regression splines. Expert Syst Appl 27 (2004) 133-142
15. Polak S., and Mendyk A. Artificial intelligence technology as a tool for initial GDM screening. Expert Syst Appl 26 (2004) 455-460
16. Rumelhart D.E., Hinton D.E., and Williams R.J. Learning internal representations by error propagation in parallel distributed processing vol. 1 (1986), MIT Press, Cambridge, MA pp. 318-62
17. Cybenko G. Approximation by superpositions of a sigmoidal Function. Mathematical Control Signal Syst 2 (1998) 303-314
18. Hornik K., Stinchcombe M., and White H. Multilayer feedforward networks are universal approximations. Neural Netw 2 (1989) 336-359
19. Vellido A., Lisboa P., and Vaughan J. Neural networks in business: a survey of applications (1992-1998). Expert Syst Appl 17 (1999) 51-70
20. Dixon J.B., and O'Brien P.E. Obesity and the white blood cell count: changes with sustained weight loss. Obes Surg 16 (2006) 251-257
21. Ziccardi P., Nappo F., Giugliano G., Esposito K., Marfella R., Cioffi M., et al. Reduction of inflammatory cytokine concentrations and improvement of endothelial functions in obese women after weight loss over one year. Circulation 105 (2002) 804-809
22. Mendez-Sanchez N., Bahena-Aponte J., Chavez-Tapia N.C., Motola-Kuba D., Sanchez-Lara K., Ponciano-Radriguez G., et al. Strong association between gallstones and cardiovascular disease. Am J Gastroenterol 100 (2005) 827-830
23. Pagliarulo M., Fornari F., Fraquelli M., Zoli M., Giangregorio F., Grigolon A., et al. Gallstone disease and related risk factors in a large cohort of diabetic patients. Dig Liver Dis 36 (2004) 130-134
24. Fraquelli M., Pagliarulo M., Colucci A., Paggi S., and Conte D. Gallblader motility in obesity, diabetes mellitus and coeliac disease. Dig Liver Dis 35 (2004) S12-S16
25. Nervi F., Miquel J.F., Alvarez M., Ferreccio C., Garcia-Zattera M.J., Gonzalez R., et al. Gallbladder disease is associated with insulin resistance in a high risk hispanic population. J Hepatology 45 (2006) 299-305
26. Csendes A., Burdiles P., Smok G., Csendes P., Burgos A., and Recio M. Histologic findings of gallbladder mucosa in 87 patients with morbid obesity without gallstones compared to 87 control subjects. J Gastrointest Surg 7 (2003) 547-551
27. Csendes A., Smok G., Burdiles P., Diaz J.C., Maluenda F., and Kornet O. Histological findings of gallbladder mucosa in 95 control subjects and 80 patients with asymptomatic gallstones. Digestive Dis Sci 43 (1998) 931-934
28. Sheen I.-S., and Liaw Y.-F. The prevalence and incidence of cholecystolithiasis in patients with chronic liver diseases: a prospective study. Hepatology 9 (1989) 538-540
29. Freeman R.V., Eagle K.A., Bates E.R., Werns S.W., Kline R.E., Karavite D., et al. Comparison of artificial neural networks with logistic regression in prediction of in-hospital death after percutaneous transluminal coronary angioplasty. Am Heart J 140 (2002) 511-520
30. Zhang G., Patuwo B.E., and Hu M.Y. Forecasting with artificial neural networks: the state of the art. Int J Forecasting 14 (1998) 35-62
31. Dayhoff J.E., and Deleo J.M. Artificial neural network-opening the black box. Cancer 91 (2001) 1615-1635
32. Paul R.R., Mukherjee A., Dutta P.K., Banerjee S., Pal M., Chatterjee J., et al. A novel wavelet neural network based pathological stage detection technique for an oral precancerous condition. J Clin Pathol 58 (2005) 932-938