154 related articles for article (PubMed ID: 37100507)
1. Gynecological cancer prognosis using machine learning techniques: A systematic review of the last three decades (1990-2022).
Sheehy J; Rutledge H; Acharya UR; Loh HW; Gururajan R; Tao X; Zhou X; Li Y; Gurney T; Kondalsamy-Chennakesavan S
Artif Intell Med; 2023 May; 139():102536. PubMed ID: 37100507
[TBL] [Abstract][Full Text] [Related]
2. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
[TBL] [Abstract][Full Text] [Related]
3. Machine learning applications in gynecological cancer: A critical review.
Fiste O; Liontos M; Zagouri F; Stamatakos G; Dimopoulos MA
Crit Rev Oncol Hematol; 2022 Nov; 179():103808. PubMed ID: 36087852
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Reporting and risk of bias of prediction models based on machine learning methods in preterm birth: A systematic review.
Yang Q; Fan X; Cao X; Hao W; Lu J; Wei J; Tian J; Yin M; Ge L
Acta Obstet Gynecol Scand; 2023 Jan; 102(1):7-14. PubMed ID: 36397723
[TBL] [Abstract][Full Text] [Related]
6. Prediction of Complications and Prognostication in Perioperative Medicine: A Systematic Review and PROBAST Assessment of Machine Learning Tools.
Arina P; Kaczorek MR; Hofmaenner DA; Pisciotta W; Refinetti P; Singer M; Mazomenos EB; Whittle J
Anesthesiology; 2024 Jan; 140(1):85-101. PubMed ID: 37944114
[TBL] [Abstract][Full Text] [Related]
7. Prognostic models for newly-diagnosed chronic lymphocytic leukaemia in adults: a systematic review and meta-analysis.
Kreuzberger N; Damen JA; Trivella M; Estcourt LJ; Aldin A; Umlauff L; Vazquez-Montes MD; Wolff R; Moons KG; Monsef I; Foroutan F; Kreuzer KA; Skoetz N
Cochrane Database Syst Rev; 2020 Jul; 7(7):CD012022. PubMed ID: 32735048
[TBL] [Abstract][Full Text] [Related]
8. Application of artificial intelligence in gynecologic malignancies: A review.
Sone K; Toyohara Y; Taguchi A; Miyamoto Y; Tanikawa M; Uchino-Mori M; Iriyama T; Tsuruga T; Osuga Y
J Obstet Gynaecol Res; 2021 Aug; 47(8):2577-2585. PubMed ID: 33973305
[TBL] [Abstract][Full Text] [Related]
9. Machine learning in the identification of prognostic DNA methylation biomarkers among patients with cancer: A systematic review of epigenome-wide studies.
Yuan T; Edelmann D; Fan Z; Alwers E; Kather JN; Brenner H; Hoffmeister M
Artif Intell Med; 2023 Sep; 143():102589. PubMed ID: 37673571
[TBL] [Abstract][Full Text] [Related]
10. Artificial intelligence and allied subsets in early detection and preclusion of gynecological cancers.
Garg P; Mohanty A; Ramisetty S; Kulkarni P; Horne D; Pisick E; Salgia R; Singhal SS
Biochim Biophys Acta Rev Cancer; 2023 Nov; 1878(6):189026. PubMed ID: 37980945
[TBL] [Abstract][Full Text] [Related]
11. Machine Learning-based Prediction Models for Diagnosis and Prognosis in Inflammatory Bowel Diseases: A Systematic Review.
Nguyen NH; Picetti D; Dulai PS; Jairath V; Sandborn WJ; Ohno-Machado L; Chen PL; Singh S
J Crohns Colitis; 2022 Mar; 16(3):398-413. PubMed ID: 34492100
[TBL] [Abstract][Full Text] [Related]
12. An Assessment of the Predictive Performance of Current Machine Learning-Based Breast Cancer Risk Prediction Models: Systematic Review.
Gao Y; Li S; Jin Y; Zhou L; Sun S; Xu X; Li S; Yang H; Zhang Q; Wang Y
JMIR Public Health Surveill; 2022 Dec; 8(12):e35750. PubMed ID: 36426919
[TBL] [Abstract][Full Text] [Related]
13. Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review.
Andaur Navarro CL; Damen JAA; Takada T; Nijman SWJ; Dhiman P; Ma J; Collins GS; Bajpai R; Riley RD; Moons KGM; Hooft L
BMJ; 2021 Oct; 375():n2281. PubMed ID: 34670780
[TBL] [Abstract][Full Text] [Related]
14. Prediction models applying machine learning to oral cavity cancer outcomes: A systematic review.
Adeoye J; Tan JY; Choi SW; Thomson P
Int J Med Inform; 2021 Oct; 154():104557. PubMed ID: 34455119
[TBL] [Abstract][Full Text] [Related]
15. Cardiovascular complications in a diabetes prediction model using machine learning: a systematic review.
Kee OT; Harun H; Mustafa N; Abdul Murad NA; Chin SF; Jaafar R; Abdullah N
Cardiovasc Diabetol; 2023 Jan; 22(1):13. PubMed ID: 36658644
[TBL] [Abstract][Full Text] [Related]
16. Prediction of hypertension using traditional regression and machine learning models: A systematic review and meta-analysis.
Chowdhury MZI; Naeem I; Quan H; Leung AA; Sikdar KC; O'Beirne M; Turin TC
PLoS One; 2022; 17(4):e0266334. PubMed ID: 35390039
[TBL] [Abstract][Full Text] [Related]
17. The comparative and added prognostic value of biomarkers to the Revised Cardiac Risk Index for preoperative prediction of major adverse cardiac events and all-cause mortality in patients who undergo noncardiac surgery.
Vernooij LM; van Klei WA; Moons KG; Takada T; van Waes J; Damen JA
Cochrane Database Syst Rev; 2021 Dec; 12(12):CD013139. PubMed ID: 34931303
[TBL] [Abstract][Full Text] [Related]
18. Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers.
Kawakami E; Tabata J; Yanaihara N; Ishikawa T; Koseki K; Iida Y; Saito M; Komazaki H; Shapiro JS; Goto C; Akiyama Y; Saito R; Saito M; Takano H; Yamada K; Okamoto A
Clin Cancer Res; 2019 May; 25(10):3006-3015. PubMed ID: 30979733
[TBL] [Abstract][Full Text] [Related]
19. Predicting breast cancer 5-year survival using machine learning: A systematic review.
Li J; Zhou Z; Dong J; Fu Y; Li Y; Luan Z; Peng X
PLoS One; 2021; 16(4):e0250370. PubMed ID: 33861809
[TBL] [Abstract][Full Text] [Related]
20. Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers.
Deist TM; Dankers FJWM; Valdes G; Wijsman R; Hsu IC; Oberije C; Lustberg T; van Soest J; Hoebers F; Jochems A; El Naqa I; Wee L; Morin O; Raleigh DR; Bots W; Kaanders JH; Belderbos J; Kwint M; Solberg T; Monshouwer R; Bussink J; Dekker A; Lambin P
Med Phys; 2018 Jul; 45(7):3449-3459. PubMed ID: 29763967
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
