366 related articles for article (PubMed ID: 34670780)
1. 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]
2. Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis.
Reeve K; On BI; Havla J; Burns J; Gosteli-Peter MA; Alabsawi A; Alayash Z; Götschi A; Seibold H; Mansmann U; Held U
Cochrane Database Syst Rev; 2023 Sep; 9(9):CD013606. PubMed ID: 37681561
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. 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]
5. Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques.
Andaur Navarro CL; Damen JAAG; Takada T; Nijman SWJ; Dhiman P; Ma J; Collins GS; Bajpai R; Riley RD; Moons KG; Hooft L
BMJ Open; 2020 Nov; 10(11):e038832. PubMed ID: 33177137
[TBL] [Abstract][Full Text] [Related]
6. Completeness of reporting of clinical prediction models developed using supervised machine learning: a 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
BMC Med Res Methodol; 2022 Jan; 22(1):12. PubMed ID: 35026997
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models.
Andaur Navarro CL; Damen JAA; van Smeden M; Takada T; Nijman SWJ; Dhiman P; Ma J; Collins GS; Bajpai R; Riley RD; Moons KGM; Hooft L
J Clin Epidemiol; 2023 Feb; 154():8-22. PubMed ID: 36436815
[TBL] [Abstract][Full Text] [Related]
10. Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence.
Collins GS; Dhiman P; Andaur Navarro CL; Ma J; Hooft L; Reitsma JB; Logullo P; Beam AL; Peng L; Van Calster B; van Smeden M; Riley RD; Moons KG
BMJ Open; 2021 Jul; 11(7):e048008. PubMed ID: 34244270
[TBL] [Abstract][Full Text] [Related]
11. Prognostic models for predicting relapse or recurrence of major depressive disorder in adults.
Moriarty AS; Meader N; Snell KI; Riley RD; Paton LW; Chew-Graham CA; Gilbody S; Churchill R; Phillips RS; Ali S; McMillan D
Cochrane Database Syst Rev; 2021 May; 5(5):CD013491. PubMed ID: 33956992
[TBL] [Abstract][Full Text] [Related]
12. Current state and completeness of reporting clinical prediction models using machine learning in systemic lupus erythematosus: A systematic review.
Munguía-Realpozo P; Etchegaray-Morales I; Mendoza-Pinto C; Méndez-Martínez S; Osorio-Peña ÁD; Ayón-Aguilar J; García-Carrasco M
Autoimmun Rev; 2023 May; 22(5):103294. PubMed ID: 36791873
[TBL] [Abstract][Full Text] [Related]
13. Outcome prediction models incorporating clinical variables for Head and Neck Squamous cell Carcinoma: A systematic review of methodological conduct and risk of bias.
Aly F; Hansen CR; Al Mouiee D; Sundaresan P; Haidar A; Vinod S; Holloway L
Radiother Oncol; 2023 Jun; 183():109629. PubMed ID: 36934895
[TBL] [Abstract][Full Text] [Related]
14. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal.
Wynants L; Van Calster B; Collins GS; Riley RD; Heinze G; Schuit E; Bonten MMJ; Dahly DL; Damen JAA; Debray TPA; de Jong VMT; De Vos M; Dhiman P; Haller MC; Harhay MO; Henckaerts L; Heus P; Kammer M; Kreuzberger N; Lohmann A; Luijken K; Ma J; Martin GP; McLernon DJ; Andaur Navarro CL; Reitsma JB; Sergeant JC; Shi C; Skoetz N; Smits LJM; Snell KIE; Sperrin M; Spijker R; Steyerberg EW; Takada T; Tzoulaki I; van Kuijk SMJ; van Bussel B; van der Horst ICC; van Royen FS; Verbakel JY; Wallisch C; Wilkinson J; Wolff R; Hooft L; Moons KGM; van Smeden M
BMJ; 2020 Apr; 369():m1328. PubMed ID: 32265220
[TBL] [Abstract][Full Text] [Related]
15. Machine learning models for diabetes management in acute care using electronic medical records: A systematic review.
Kamel Rahimi A; Canfell OJ; Chan W; Sly B; Pole JD; Sullivan C; Shrapnel S
Int J Med Inform; 2022 Apr; 162():104758. PubMed ID: 35398812
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Missing data is poorly handled and reported in prediction model studies using machine learning: a literature review.
Nijman S; Leeuwenberg AM; Beekers I; Verkouter I; Jacobs J; Bots ML; Asselbergs FW; Moons K; Debray T
J Clin Epidemiol; 2022 Feb; 142():218-229. PubMed ID: 34798287
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. 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]
[Next] [New Search]