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Cited by in F6Publishing
For: De Silva K, Enticott J, Barton C, Forbes A, Saha S, Nikam R. Use and performance of machine learning models for type 2 diabetes prediction in clinical and community care settings: Protocol for a systematic review and meta-analysis of predictive modeling studies. Digit Health 2021;7:20552076211047390. [PMID: 34868616 DOI: 10.1177/20552076211047390] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Oliva A, Altamura G, Nurchis MC, Zedda M, Sessa G, Cazzato F, Aulino G, Sapienza M, Riccardi MT, Della Morte G, Caputo M, Grassi S, Damiani G. Assessing the potentiality of algorithms and artificial intelligence adoption to disrupt patient primary care with a safer and faster medication management: a systematic review protocol. BMJ Open 2022;12:e057399. [PMID: 35580973 DOI: 10.1136/bmjopen-2021-057399] [Reference Citation Analysis]
2 Benítez-andrades JA, García-ordás MT, Álvarez-gonzález M, Leirós-rodríguez R, López Rodríguez AF. Detection of the most influential variables for preventing postpartum urinary incontinence using machine learning techniques. DIGITAL HEALTH 2022;8:205520762211112. [DOI: 10.1177/20552076221111289] [Reference Citation Analysis]