BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Braccioni F, Bottigliengo D, Ermolao A, Schiavon M, Loy M, Marchi MR, Gregori D, Rea F, Vianello A. Dyspnea, effort and muscle pain during exercise in lung transplant recipients: an analysis of their association with cardiopulmonary function parameters using machine learning. Respir Res 2020;21:267. [PMID: 33059678 DOI: 10.1186/s12931-020-01535-5] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Camargo E, Aguilar J, Quintero Y, Rivas F, Ardila D. An incremental learning approach to prediction models of SEIRD variables in the context of the COVID-19 pandemic. Health Technol . [DOI: 10.1007/s12553-022-00668-5] [Reference Citation Analysis]
2 Inbar O, Inbar O, Reuveny R, Segel MJ, Greenspan H, Scheinowitz M. A Machine Learning Approach to the Interpretation of Cardiopulmonary Exercise Tests: Development and Validation. Pulm Med 2021;2021:5516248. [PMID: 34158976 DOI: 10.1155/2021/5516248] [Reference Citation Analysis]
3 Huang F, Leng X, Kasukurthi MV, Huang Y, Li D, Tan S, Lu G, Lu J, Benton RG, Borchert GM, Huang J. Utilizing Machine Learning Techniques to Predict the Efficacy of Aerobic Exercise Intervention on Young Hypertensive Patients Based on Cardiopulmonary Exercise Testing. J Healthc Eng 2021;2021:6633832. [PMID: 33968353 DOI: 10.1155/2021/6633832] [Reference Citation Analysis]