385 related articles for article (PubMed ID: 34492100)
1. 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]
2. 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]
3. Artificial intelligence image-based prediction models in IBD exhibit high risk of bias: A systematic review.
Liu X; Reigle J; Prasath VBS; Dhaliwal J
Comput Biol Med; 2024 Mar; 171():108093. PubMed ID: 38354499
[TBL] [Abstract][Full Text] [Related]
4. Big data in IBD: big progress for clinical practice.
Seyed Tabib NS; Madgwick M; Sudhakar P; Verstockt B; Korcsmaros T; Vermeire S
Gut; 2020 Aug; 69(8):1520-1532. PubMed ID: 32111636
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Gut microbiome-based supervised machine learning for clinical diagnosis of inflammatory bowel diseases.
Manandhar I; Alimadadi A; Aryal S; Munroe PB; Joe B; Cheng X
Am J Physiol Gastrointest Liver Physiol; 2021 Mar; 320(3):G328-G337. PubMed ID: 33439104
[TBL] [Abstract][Full Text] [Related]
7. Predicting inpatient mortality in patients with inflammatory bowel disease: A machine learning approach.
Charilaou P; Mohapatra S; Doukas S; Kohli M; Radadiya D; Devani K; Broder A; Elemento O; Lukin DJ; Battat R
J Gastroenterol Hepatol; 2023 Feb; 38(2):241-250. PubMed ID: 36258306
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Machine Learning Predictive Outcomes Modeling in Inflammatory Bowel Diseases.
Javaid A; Shahab O; Adorno W; Fernandes P; May E; Syed S
Inflamm Bowel Dis; 2022 Jun; 28(6):819-829. PubMed ID: 34417815
[TBL] [Abstract][Full Text] [Related]
10. Machine-learning versus traditional approaches for atherosclerotic cardiovascular risk prognostication in primary prevention cohorts: a systematic review and meta-analysis.
Liu W; Laranjo L; Klimis H; Chiang J; Yue J; Marschner S; Quiroz JC; Jorm L; Chow CK
Eur Heart J Qual Care Clin Outcomes; 2023 Jun; 9(4):310-322. PubMed ID: 36869800
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. 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]
13. Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review.
Dhiman P; Ma J; Andaur Navarro CL; Speich B; Bullock G; Damen JAA; Hooft L; Kirtley S; Riley RD; Van Calster B; Moons KGM; Collins GS
BMC Med Res Methodol; 2022 Apr; 22(1):101. PubMed ID: 35395724
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. A machine learning approach identifies 5-ASA and ulcerative colitis as being linked with higher COVID-19 mortality in patients with IBD.
Roy S; Sheikh SZ; Furey TS
Sci Rep; 2021 Aug; 11(1):16522. PubMed ID: 34389789
[TBL] [Abstract][Full Text] [Related]
16. Machine learning models for predicting acute kidney injury: a systematic review and critical appraisal.
Vagliano I; Chesnaye NC; Leopold JH; Jager KJ; Abu-Hanna A; Schut MC
Clin Kidney J; 2022 Dec; 15(12):2266-2280. PubMed ID: 36381375
[TBL] [Abstract][Full Text] [Related]
17. Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.
Awaysheh A; Wilcke J; Elvinger F; Rees L; Fan W; Zimmerman KL
J Vet Diagn Invest; 2016 Nov; 28(6):679-687. PubMed ID: 27698168
[TBL] [Abstract][Full Text] [Related]
18. Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic review.
Gonzalez R; Nejat P; Saha A; Campbell CJV; Norgan AP; Lokker C
J Pathol Inform; 2024 Dec; 15():100348. PubMed ID: 38089005
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Machine Learning Modeling from Omics Data as Prospective Tool for Improvement of Inflammatory Bowel Disease Diagnosis and Clinical Classifications.
Stankovic B; Kotur N; Nikcevic G; Gasic V; Zukic B; Pavlovic S
Genes (Basel); 2021 Sep; 12(9):. PubMed ID: 34573420
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]