237 related articles for article (PubMed ID: 37673576)
21. Mature artificial intelligence- and machine learning-enabled medical tools impacting vascular surgical care: A scoping review of late-stage, US Food and Drug Administration-approved or cleared technologies relevant to vascular surgeons.
Stonko DP; Hicks CW
Semin Vasc Surg; 2023 Sep; 36(3):460-470. PubMed ID: 37863621
[TBL] [Abstract][Full Text] [Related]
22. Artificial intelligence-based methods for fusion of electronic health records and imaging data.
Mohsen F; Ali H; El Hajj N; Shah Z
Sci Rep; 2022 Oct; 12(1):17981. PubMed ID: 36289266
[TBL] [Abstract][Full Text] [Related]
23. Application and performance of artificial intelligence technology in cytopathology.
Alrafiah AR
Acta Histochem; 2022 May; 124(4):151890. PubMed ID: 35366580
[TBL] [Abstract][Full Text] [Related]
24. The use of artificial intelligence and machine learning methods in early pregnancy pre-eclampsia screening: A systematic review protocol.
Hedley PL; Hagen CM; Wilstrup C; Christiansen M
PLoS One; 2023; 18(4):e0272465. PubMed ID: 37079505
[TBL] [Abstract][Full Text] [Related]
25. Taxonomy of hybrid architectures involving rule-based reasoning and machine learning in clinical decision systems: A scoping review.
Kierner S; Kucharski J; Kierner Z
J Biomed Inform; 2023 Aug; 144():104428. PubMed ID: 37355025
[TBL] [Abstract][Full Text] [Related]
26. Registration, publication, and outcome reporting among pivotal clinical trials that supported FDA approval of high-risk cardiovascular devices before and after FDAAA.
Swanson MJ; Johnston JL; Ross JS
Trials; 2021 Nov; 22(1):817. PubMed ID: 34789308
[TBL] [Abstract][Full Text] [Related]
27. Prediction of Drug Approval After Phase I Clinical Trials in Oncology: RESOLVED2.
Beinse G; Tellier V; Charvet V; Deutsch E; Borget I; Massard C; Hollebecque A; Verlingue L
JCO Clin Cancer Inform; 2019 Sep; 3():1-10. PubMed ID: 31539266
[TBL] [Abstract][Full Text] [Related]
28. Value Proposition of FDA-Approved Artificial Intelligence Algorithms for Neuroimaging.
Bajaj S; Khunte M; Moily NS; Payabvash S; Wintermark M; Gandhi D; Malhotra A
J Am Coll Radiol; 2023 Dec; 20(12):1241-1249. PubMed ID: 37574094
[TBL] [Abstract][Full Text] [Related]
29. The future of Cochrane Neonatal.
Soll RF; Ovelman C; McGuire W
Early Hum Dev; 2020 Nov; 150():105191. PubMed ID: 33036834
[TBL] [Abstract][Full Text] [Related]
30. The State of Artificial Intelligence in Pediatric Surgery: A Systematic Review.
Elahmedi M; Sawhney R; Guadagno E; Botelho F; Poenaru D
J Pediatr Surg; 2024 May; 59(5):774-782. PubMed ID: 38418276
[TBL] [Abstract][Full Text] [Related]
31. Machine learning and the electrocardiogram over two decades: Time series and meta-analysis of the algorithms, evaluation metrics and applications.
Rjoob K; Bond R; Finlay D; McGilligan V; Leslie SJ; Rababah A; Iftikhar A; Guldenring D; Knoery C; McShane A; Peace A; Macfarlane PW
Artif Intell Med; 2022 Oct; 132():102381. PubMed ID: 36207087
[TBL] [Abstract][Full Text] [Related]
32. Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.
Woldaregay AZ; Årsand E; Walderhaug S; Albers D; Mamykina L; Botsis T; Hartvigsen G
Artif Intell Med; 2019 Jul; 98():109-134. PubMed ID: 31383477
[TBL] [Abstract][Full Text] [Related]
33. Artificial Intelligence in Perioperative Medicine: A Proposed Common Language With Applications to FDA-Approved Devices.
Melvin RL; Broyles MG; Duggan EW; John S; Smith AD; Berkowitz DE
Front Digit Health; 2022; 4():872675. PubMed ID: 35547090
[TBL] [Abstract][Full Text] [Related]
34. How do Orthopaedic Devices Change After Their Initial FDA Premarket Approval?
Samuel AM; Rathi VK; Grauer JN; Ross JS
Clin Orthop Relat Res; 2016 Apr; 474(4):1053-68. PubMed ID: 26584802
[TBL] [Abstract][Full Text] [Related]
35. Artificial Intelligence for Hip Fracture Detection and Outcome Prediction: A Systematic Review and Meta-analysis.
Lex JR; Di Michele J; Koucheki R; Pincus D; Whyne C; Ravi B
JAMA Netw Open; 2023 Mar; 6(3):e233391. PubMed ID: 36930153
[TBL] [Abstract][Full Text] [Related]
36. A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging.
Mervak BM; Fried JG; Wasnik AP
Diagnostics (Basel); 2023 Sep; 13(18):. PubMed ID: 37761253
[TBL] [Abstract][Full Text] [Related]
37. Machine learning models for predicting pre-eclampsia: a systematic review protocol.
Ranjbar A; Taeidi E; Mehrnoush V; Roozbeh N; Darsareh F
BMJ Open; 2023 Sep; 13(9):e074705. PubMed ID: 37696628
[TBL] [Abstract][Full Text] [Related]
38. Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews.
Martinez-Millana A; Saez-Saez A; Tornero-Costa R; Azzopardi-Muscat N; Traver V; Novillo-Ortiz D
Int J Med Inform; 2022 Oct; 166():104855. PubMed ID: 35998421
[TBL] [Abstract][Full Text] [Related]
39. Are current clinical studies on artificial intelligence-based medical devices comprehensive enough to support a full health technology assessment? A systematic review.
Farah L; Davaze-Schneider J; Martin T; Nguyen P; Borget I; Martelli N
Artif Intell Med; 2023 Jun; 140():102547. PubMed ID: 37210155
[TBL] [Abstract][Full Text] [Related]
40. Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future-A systematic review.
Alabi RO; Youssef O; Pirinen M; Elmusrati M; Mäkitie AA; Leivo I; Almangush A
Artif Intell Med; 2021 May; 115():102060. PubMed ID: 34001326
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
