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Cited by in F6Publishing
For: Wang L, Fan R, Zhang C, Hong L, Zhang T, Chen Y, Liu K, Wang Z, Zhong J. Applying Machine Learning Models to Predict Medication Nonadherence in Crohn's Disease Maintenance Therapy. Patient Prefer Adherence. 2020;14:917-926. [PMID: 32581518 DOI: 10.2147/ppa.s253732] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Oka A, Ishimura N, Ishihara S. A New Dawn for the Use of Artificial Intelligence in Gastroenterology, Hepatology and Pancreatology. Diagnostics (Basel) 2021;11:1719. [PMID: 34574060 DOI: 10.3390/diagnostics11091719] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
2 Spataru A, van Dommelen P, Arnaud L, Le Masne Q, Quarteroni S, Koledova E. Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device. BMC Med Inform Decis Mak 2022;22:179. [PMID: 35794586 DOI: 10.1186/s12911-022-01918-2] [Reference Citation Analysis]
3 Babel A, Taneja R, Mondello Malvestiti F, Monaco A, Donde S. Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases. Front Digit Health 2021;3:669869. [PMID: 34713142 DOI: 10.3389/fdgth.2021.669869] [Reference Citation Analysis]
4 Javaid A, Shahab O, Adorno W, Fernandes P, May E, Syed S. Machine Learning Predictive Outcomes Modeling in Inflammatory Bowel Diseases. Inflamm Bowel Dis 2021:izab187. [PMID: 34417815 DOI: 10.1093/ibd/izab187] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Tornincasa V, Dixon D, Le Masne Q, Martin B, Arnaud L, van Dommelen P, Koledova E. Integrated Digital Health Solutions in the Management of Growth Disorders in Pediatric Patients Receiving Growth Hormone Therapy: A Retrospective Analysis. Front Endocrinol 2022;13:882192. [DOI: 10.3389/fendo.2022.882192] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Gubatan J, Levitte S, Patel A, Balabanis T, Wei MT, Sinha SR. Artificial intelligence applications in inflammatory bowel disease: Emerging technologies and future directions. World J Gastroenterol 2021; 27(17): 1920-1935 [PMID: 34007130 DOI: 10.3748/wjg.v27.i17.1920] [Cited by in CrossRef: 23] [Cited by in F6Publishing: 15] [Article Influence: 23.0] [Reference Citation Analysis]
7 Stafford IS, Gosink MM, Mossotto E, Ennis S, Hauben M. A Systematic Review of Artificial Intelligence and Machine Learning Applications to Inflammatory Bowel Disease, with Practical Guidelines for Interpretation. Inflamm Bowel Dis 2022:izac115. [PMID: 35699597 DOI: 10.1093/ibd/izac115] [Reference Citation Analysis]