267 related articles for article (PubMed ID: 26701199)
1. Development of a web-based liver cancer prediction model for type II diabetes patients by using an artificial neural network.
Rau HH; Hsu CY; Lin YA; Atique S; Fuad A; Wei LM; Hsu MH
Comput Methods Programs Biomed; 2016 Mar; 125():58-65. PubMed ID: 26701199
[TBL] [Abstract][Full Text] [Related]
2. Application of serum protein fingerprinting coupled with artificial neural network model in diagnosis of hepatocellular carcinoma.
Wang JX; Zhang B; Yu JK; Liu J; Yang MQ; Zheng S
Chin Med J (Engl); 2005 Aug; 118(15):1278-84. PubMed ID: 16117882
[TBL] [Abstract][Full Text] [Related]
3. Prediction of low bone mineral density in postmenopausal women by artificial neural network model compared to logistic regression model.
Ongphiphadhanakul B; Rajatanavin R; Chailurkit L; Piaseu N; Teerarungsikul K; Sirisriro R; Komindr S; Pauvilai G
J Med Assoc Thai; 1997 Aug; 80(8):508-15. PubMed ID: 9277083
[TBL] [Abstract][Full Text] [Related]
4. Preoperative prediction of hepatocellular carcinoma tumour grade and micro-vascular invasion by means of artificial neural network: a pilot study.
Cucchetti A; Piscaglia F; Grigioni AD; Ravaioli M; Cescon M; Zanello M; Grazi GL; Golfieri R; Grigioni WF; Pinna AD
J Hepatol; 2010 Jun; 52(6):880-8. PubMed ID: 20409605
[TBL] [Abstract][Full Text] [Related]
5. Late rectal bleeding after 3D-CRT for prostate cancer: development of a neural-network-based predictive model.
Tomatis S; Rancati T; Fiorino C; Vavassori V; Fellin G; Cagna E; Mauro FA; Girelli G; Monti A; Baccolini M; Naldi G; Bianchi C; Menegotti L; Pasquino M; Stasi M; Valdagni R
Phys Med Biol; 2012 Mar; 57(5):1399-412. PubMed ID: 22349550
[TBL] [Abstract][Full Text] [Related]
6. Can we improve the prediction of stone-free status after extracorporeal shock wave lithotripsy for ureteral stones? A neural network or a statistical model?
Gomha MA; Sheir KZ; Showky S; Abdel-Khalek M; Mokhtar AA; Madbouly K
J Urol; 2004 Jul; 172(1):175-9. PubMed ID: 15201765
[TBL] [Abstract][Full Text] [Related]
7. Prediction of significant fibrosis in hepatitis C virus infected liver transplant recipients by artificial neural network analysis of clinical factors.
Piscaglia F; Cucchetti A; Benlloch S; Vivarelli M; Berenguer J; Bolondi L; Pinna AD; Berenguer M
Eur J Gastroenterol Hepatol; 2006 Dec; 18(12):1255-61. PubMed ID: 17099373
[TBL] [Abstract][Full Text] [Related]
8. Artificial neural network models for prediction of acute coronary syndromes using clinical data from the time of presentation.
Harrison RF; Kennedy RL
Ann Emerg Med; 2005 Nov; 46(5):431-9. PubMed ID: 16271675
[TBL] [Abstract][Full Text] [Related]
9. Comparison of three data mining models for prediction of advanced schistosomiasis prognosis in the Hubei province.
Li G; Zhou X; Liu J; Chen Y; Zhang H; Chen Y; Liu J; Jiang H; Yang J; Nie S
PLoS Negl Trop Dis; 2018 Feb; 12(2):e0006262. PubMed ID: 29447165
[TBL] [Abstract][Full Text] [Related]
10. Predicting mortality in patients with cirrhosis of liver with application of neural network technology.
Banerjee R; Das A; Ghoshal UC; Sinha M
J Gastroenterol Hepatol; 2003 Sep; 18(9):1054-60. PubMed ID: 12911662
[TBL] [Abstract][Full Text] [Related]
11. Evaluating the risk of type 2 diabetes mellitus using artificial neural network: an effective classification approach.
Wang C; Li L; Wang L; Ping Z; Flory MT; Wang G; Xi Y; Li W
Diabetes Res Clin Pract; 2013 Apr; 100(1):111-8. PubMed ID: 23453177
[TBL] [Abstract][Full Text] [Related]
12. Use of artificial neural networks to predict surgical satisfaction in patients with lumbar spinal canal stenosis: clinical article.
Azimi P; Benzel EC; Shahzadi S; Azhari S; Mohammadi HR
J Neurosurg Spine; 2014 Mar; 20(3):300-5. PubMed ID: 24438428
[TBL] [Abstract][Full Text] [Related]
13. Development of a prediction model for pancreatic cancer in patients with type 2 diabetes using logistic regression and artificial neural network models.
Hsieh MH; Sun LM; Lin CL; Hsieh MJ; Hsu CY; Kao CH
Cancer Manag Res; 2018; 10():6317-6324. PubMed ID: 30568493
[TBL] [Abstract][Full Text] [Related]
14. Improvement in the Prediction of Ventilator Weaning Outcomes by an Artificial Neural Network in a Medical ICU.
Kuo HJ; Chiu HW; Lee CN; Chen TT; Chang CC; Bien MY
Respir Care; 2015 Nov; 60(11):1560-9. PubMed ID: 26329358
[TBL] [Abstract][Full Text] [Related]
15. Artificial neural network for prediction of distant metastasis in colorectal cancer.
Biglarian A; Bakhshi E; Gohari MR; Khodabakhshi R
Asian Pac J Cancer Prev; 2012; 13(3):927-30. PubMed ID: 22631673
[TBL] [Abstract][Full Text] [Related]
16. Artificial neural networking model for the prediction of post-hepatectomy survival of patients with early hepatocellular carcinoma.
Qiao G; Li J; Huang A; Yan Z; Lau WY; Shen F
J Gastroenterol Hepatol; 2014 Dec; 29(12):2014-20. PubMed ID: 24989634
[TBL] [Abstract][Full Text] [Related]
17. Performance comparison between Logistic regression, decision trees, and multilayer perceptron in predicting peripheral neuropathy in type 2 diabetes mellitus.
Li CP; Zhi XY; Ma J; Cui Z; Zhu ZL; Zhang C; Hu LP
Chin Med J (Engl); 2012 Mar; 125(5):851-7. PubMed ID: 22490586
[TBL] [Abstract][Full Text] [Related]
18. A simple prediction rule and a neural network model to predict pancreatic beta-cell reserve in young adults with diabetes mellitus.
Thamprajamchit S; Ongphiphadhanakul B; Krittiyawong S; Chanprasertyothin S; Bunnag P; Rajatanavin R; Puavilai G
J Med Assoc Thai; 2001 Mar; 84(3):332-8. PubMed ID: 11460933
[TBL] [Abstract][Full Text] [Related]
19. Glaucoma diagnostics.
Geimer SA
Acta Ophthalmol; 2013 Feb; 91 Thesis 1():1-32. PubMed ID: 23384049
[TBL] [Abstract][Full Text] [Related]
20. Prediction of renal insufficiency in Pima Indians with nephropathy of type 2 diabetes mellitus.
Goldfarb-Rumyantzev AS; Pappas L
Am J Kidney Dis; 2002 Aug; 40(2):252-64. PubMed ID: 12148097
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
