209 related articles for article (PubMed ID: 37306511)
1. Use of machine learning to predict bladder cancer survival outcomes: a systematic literature review.
Liu YS; Thaliffdeen R; Han S; Park C
Expert Rev Pharmacoecon Outcomes Res; 2023; 23(7):761-771. PubMed ID: 37306511
[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. Development of robust artificial neural networks for prediction of 5-year survival in bladder cancer.
Bhambhvani HP; Zamora A; Shkolyar E; Prado K; Greenberg DR; Kasman AM; Liao J; Shah S; Srinivas S; Skinner EC; Shah JB
Urol Oncol; 2021 Mar; 39(3):193.e7-193.e12. PubMed ID: 32593506
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Cervical cancer survival prediction by machine learning algorithms: a systematic review.
Rahimi M; Akbari A; Asadi F; Emami H
BMC Cancer; 2023 Apr; 23(1):341. PubMed ID: 37055741
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Beyond the black stump: rapid reviews of health research issues affecting regional, rural and remote Australia.
Osborne SR; Alston LV; Bolton KA; Whelan J; Reeve E; Wong Shee A; Browne J; Walker T; Versace VL; Allender S; Nichols M; Backholer K; Goodwin N; Lewis S; Dalton H; Prael G; Curtin M; Brooks R; Verdon S; Crockett J; Hodgins G; Walsh S; Lyle DM; Thompson SC; Browne LJ; Knight S; Pit SW; Jones M; Gillam MH; Leach MJ; Gonzalez-Chica DA; Muyambi K; Eshetie T; Tran K; May E; Lieschke G; Parker V; Smith A; Hayes C; Dunlop AJ; Rajappa H; White R; Oakley P; Holliday S
Med J Aust; 2020 Dec; 213 Suppl 11():S3-S32.e1. PubMed ID: 33314144
[TBL] [Abstract][Full Text] [Related]
8. Current and future applications of machine and deep learning in urology: a review of the literature on urolithiasis, renal cell carcinoma, and bladder and prostate cancer.
Suarez-Ibarrola R; Hein S; Reis G; Gratzke C; Miernik A
World J Urol; 2020 Oct; 38(10):2329-2347. PubMed ID: 31691082
[TBL] [Abstract][Full Text] [Related]
9. Machine learning predictive models for acute pancreatitis: A systematic review.
Zhou Y; Ge YT; Shi XL; Wu KY; Chen WW; Ding YB; Xiao WM; Wang D; Lu GT; Hu LH
Int J Med Inform; 2022 Jan; 157():104641. PubMed ID: 34785488
[TBL] [Abstract][Full Text] [Related]
10. Machine learning in medication prescription: A systematic review.
Iancu A; Leb I; Prokosch HU; Rödle W
Int J Med Inform; 2023 Dec; 180():105241. PubMed ID: 37939541
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Machine learning vs. conventional statistical models for predicting heart failure readmission and mortality.
Shin S; Austin PC; Ross HJ; Abdel-Qadir H; Freitas C; Tomlinson G; Chicco D; Mahendiran M; Lawler PR; Billia F; Gramolini A; Epelman S; Wang B; Lee DS
ESC Heart Fail; 2021 Feb; 8(1):106-115. PubMed ID: 33205591
[TBL] [Abstract][Full Text] [Related]
13. Application of machine learning in predicting survival outcomes involving real-world data: a scoping review.
Huang Y; Li J; Li M; Aparasu RR
BMC Med Res Methodol; 2023 Nov; 23(1):268. PubMed ID: 37957593
[TBL] [Abstract][Full Text] [Related]
14. Predicting lung cancer survival based on clinical data using machine learning: A review.
Altuhaifa FA; Win KT; Su G
Comput Biol Med; 2023 Oct; 165():107338. PubMed ID: 37625260
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. 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]
17. Gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer: an evidence-based and economic analysis.
Medical Advisory Secretariat
Ont Health Technol Assess Ser; 2010; 10(23):1-57. PubMed ID: 23074401
[TBL] [Abstract][Full Text] [Related]
18. Optimizing prognostic factors of five-year survival in gastric cancer patients using feature selection techniques with machine learning algorithms: a comparative study.
Afrash MR; Mirbagheri E; Mashoufi M; Kazemi-Arpanahi H
BMC Med Inform Decis Mak; 2023 Apr; 23(1):54. PubMed ID: 37024885
[TBL] [Abstract][Full Text] [Related]
19. Systematic review of approaches to use of neighborhood-level risk factors with clinical data to predict clinical risk and recommend interventions.
Wilkinson K; Sheets L; Fitch D; Popejoy L
J Biomed Inform; 2021 Apr; 116():103713. PubMed ID: 33610880
[TBL] [Abstract][Full Text] [Related]
20. Machine learning techniques for mortality prediction in emergency departments: a systematic review.
Naemi A; Schmidt T; Mansourvar M; Naghavi-Behzad M; Ebrahimi A; Wiil UK
BMJ Open; 2021 Nov; 11(11):e052663. PubMed ID: 34728454
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
