183 related articles for article (PubMed ID: 26109965)
21. A Machine Learning Model for Detection of Coronary Artery Disease Using Noninvasive Clinical Parameters.
Sayadi M; Varadarajan V; Sadoughi F; Chopannejad S; Langarizadeh M
Life (Basel); 2022 Nov; 12(11):. PubMed ID: 36431068
[No Abstract] [Full Text] [Related]
22. Decision tree-based diagnosis of coronary artery disease: CART model.
Ghiasi MM; Zendehboudi S; Mohsenipour AA
Comput Methods Programs Biomed; 2020 Aug; 192():105400. PubMed ID: 32179311
[TBL] [Abstract][Full Text] [Related]
23. Non-invasive detection of coronary artery disease in high-risk patients based on the stenosis prediction of separate coronary arteries.
Alizadehsani R; Hosseini MJ; Khosravi A; Khozeimeh F; Roshanzamir M; Sarrafzadegan N; Nahavandi S
Comput Methods Programs Biomed; 2018 Aug; 162():119-127. PubMed ID: 29903478
[TBL] [Abstract][Full Text] [Related]
24. Fuzzy based expert system for diagnosis of coronary artery disease in nigeria.
Muhammad LJ; Algehyne EA
Health Technol (Berl); 2021; 11(2):319-329. PubMed ID: 33614390
[TBL] [Abstract][Full Text] [Related]
25. Diagnosing Coronary Artery Disease on the Basis of Hard Ensemble Voting Optimization.
Mohammedqasim H; Mohammedqasem R; Ata O; Alyasin EI
Medicina (Kaunas); 2022 Nov; 58(12):. PubMed ID: 36556946
[TBL] [Abstract][Full Text] [Related]
26. Multidetector computed tomography for coronary artery disease screening in asymptomatic populations: evidence-based analysis.
Medical Advisory Secretariat
Ont Health Technol Assess Ser; 2007; 7(3):1-56. PubMed ID: 23074503
[TBL] [Abstract][Full Text] [Related]
27. Detection of coronary artery disease by reduced features and extreme learning machine.
Singh RS; Saini BS; Sunkaria RK
Clujul Med; 2018; 91(2):166-175. PubMed ID: 29785154
[TBL] [Abstract][Full Text] [Related]
28. Machine learning-based coronary artery disease diagnosis: A comprehensive review.
Alizadehsani R; Abdar M; Roshanzamir M; Khosravi A; Kebria PM; Khozeimeh F; Nahavandi S; Sarrafzadegan N; Acharya UR
Comput Biol Med; 2019 Aug; 111():103346. PubMed ID: 31288140
[TBL] [Abstract][Full Text] [Related]
29. Automated diagnosis of coronary artery disease based on data mining and fuzzy modeling.
Tsipouras MG; Exarchos TP; Fotiadis DI; Kotsia AP; Vakalis KV; Naka KK; Michalis LK
IEEE Trans Inf Technol Biomed; 2008 Jul; 12(4):447-58. PubMed ID: 18632325
[TBL] [Abstract][Full Text] [Related]
30. Development of a Non-Invasive Machine-Learned Point-of-Care Rule-Out Test for Coronary Artery Disease.
Burton T; Fathieh F; Nemati N; Gillins HR; Shadforth IP; Ramchandani S; Bridges CR
Diagnostics (Basel); 2024 Mar; 14(7):. PubMed ID: 38611631
[TBL] [Abstract][Full Text] [Related]
31. Application of fuzzy-classifier system to coronary artery disease and breast cancer.
Jain R; Mazumdar J; Moran W
Australas Phys Eng Sci Med; 1998 Sep; 21(3):141-7. PubMed ID: 9848948
[TBL] [Abstract][Full Text] [Related]
32. Generating fuzzy rules for constructing interpretable classifier of diabetes disease.
Settouti N; Chikh MA; Saidi M
Australas Phys Eng Sci Med; 2012 Sep; 35(3):257-70. PubMed ID: 22895813
[TBL] [Abstract][Full Text] [Related]
33. Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.
Jiménez F; Sánchez G; Juárez JM
Artif Intell Med; 2014 Mar; 60(3):197-219. PubMed ID: 24525210
[TBL] [Abstract][Full Text] [Related]
34. A mathematical theory of shape and neuro-fuzzy methodology-based diagnostic analysis: a comparative study on early detection and treatment planning of brain cancer.
Kar S; Majumder DD
Int J Clin Oncol; 2017 Aug; 22(4):667-681. PubMed ID: 28321787
[TBL] [Abstract][Full Text] [Related]
35. Quantification of coronary arterial stenoses in CTA using fuzzy distance transform.
Xu Y; Liang G; Hu G; Yang Y; Geng J; Saha PK
Comput Med Imaging Graph; 2012 Jan; 36(1):11-24. PubMed ID: 21555207
[TBL] [Abstract][Full Text] [Related]
36. Deep learning to detect significant coronary artery disease from plain chest radiographs AI4CAD.
D'Ancona G; Massussi M; Savardi M; Signoroni A; Di Bacco L; Farina D; Metra M; Maroldi R; Muneretto C; Ince H; Costabile D; Murero M; Chizzola G; Curello S; Benussi S
Int J Cardiol; 2023 Jan; 370():435-441. PubMed ID: 36343794
[TBL] [Abstract][Full Text] [Related]
37. A simple validated clinical tool to predict the absence of coronary artery disease in patients with systolic heart failure of unclear etiology.
Doukky R; Shih MJ; Rahaby M; Alyousef T; Abusin S; Ansari NH; Kelly RF
Am J Cardiol; 2013 Oct; 112(8):1165-70. PubMed ID: 23891428
[TBL] [Abstract][Full Text] [Related]
38. A hybrid intelligent system for diagnosing microalbuminuria in type 2 diabetes patients without having to measure urinary albumin.
Marateb HR; Mansourian M; Faghihimani E; Amini M; Farina D
Comput Biol Med; 2014 Feb; 45():34-42. PubMed ID: 24480161
[TBL] [Abstract][Full Text] [Related]
39. Design of fuzzy classifier for diabetes disease using Modified Artificial Bee Colony algorithm.
Beloufa F; Chikh MA
Comput Methods Programs Biomed; 2013 Oct; 112(1):92-103. PubMed ID: 23932385
[TBL] [Abstract][Full Text] [Related]
40. Accuracy of cardiac magnetic resonance imaging to rule out significant coronary artery disease in patients with systolic heart failure of unknown aetiology: Single-centre experience and comprehensive meta-analysis.
Manchuelle A; Pontana F; De Groote P; Lebert P; Fertin M; Baijot M; Hurt C; Lamblin N; Debry N; Schurtz G; Pentiah AD; Sudre A; Remy-Jardin M; Lancellotti P; Van Belle E; Bauters C; Lemesle G; Delhaye C
Arch Cardiovasc Dis; 2018 Nov; 111(11):686-701. PubMed ID: 29861294
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]