This paper is in the following e-collection/theme issue:

#xPharmacologyandTherapeutics (2) Digital Health Reviews (1174) Machine Learning (1373) Artificial Intelligence (1188) Medication Adherence (72) Tools, Programs and Algorithms (237)

Published on in Vol 2, No 4 (2021): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26993, first published .
Machine Learning and Medication Adherence: Scoping Review

Machine Learning and Medication Adherence: Scoping Review

Machine Learning and Medication Adherence: Scoping Review

Authors of this article:

Aaron Bohlmann1 Author Orcid Image ;   Javed Mostafa1 Author Orcid Image ;   Manish Kumar1, 2 Author Orcid Image
Article Authors Cited by (13) Tweetations (2) Metrics

Journals

  1. Kwan Y. Peer Review of “Machine Learning and Medication Adherence: Scoping Review”. JMIRx Med 2021;2(4):e33963 View
  2. Bohlmann A, Mostafa J, Kumar M. Authors' Responses to Peer Review of “Machine Learning and Medication Adherence: Scoping Review”. JMIRx Med 2021;2(4):e33962 View
  3. Kardas P. Peer Review of “Machine Learning and Medication Adherence: Scoping Review”. JMIRx Med 2021;2(4):e33965 View
  4. Phan P, Abad C. The future of AI in health-care quality: defining the challenges and opportunities moving forward. International Journal for Quality in Health Care 2022;34(4) View
  5. Masiero M, Spada G, Sanchini V, Munzone E, Pietrobon R, Teixeira L, Valencia M, Machiavelli A, Fragale E, Pezzolato M, Pravettoni G. A Machine Learning Model to Predict Patients’ Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2023;12:e48852 View
  6. Yadav S, Yadav S, Verma P, Ojha S, Mishra S. Artificial Intelligence: An Advanced Evolution In Forensic and Criminal Investigation. Current Forensic Science 2022;1 View
  7. van Breugel M, Fehrmann R, Bügel M, Rezwan F, Holloway J, Nawijn M, Fontanella S, Custovic A, Koppelman G. Current state and prospects of artificial intelligence in allergy. Allergy 2023;78(10):2623 View
  8. Ekpezu A, Wiafe I, Oinas-Kukkonen H. Predicting Adherence to Behavior Change Support Systems Using Machine Learning: Systematic Review. JMIR AI 2023;2:e46779 View
  9. Georges Badr N, Khiami M, Carrubbo L, Le Dinh T. Improving access to prescription-based care through patient-centered smart pharmacy ecosystems. ITM Web of Conferences 2024;62:02003 View
  10. Rodriguez D, Chen J, Viswanadham R, Lawrence K, Mann D. Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: An Evaluation Study (Preprint). JMIR AI 2023 View
  11. Masiero M, Spada G, Fragale E, Pezzolato M, Munzone E, Sanchini V, Pietrobon R, Teixeira L, Valencia M, Machiavelli A, Woloski R, Marzorati C, Pravettoni G. Adherence to oral anticancer treatments: network and sentiment analysis exploring perceived internal and external determinants in patients with metastatic breast cancer. Supportive Care in Cancer 2024;32(7) View