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

Artificial Intelligence (1371) Digital Health Reviews (1289) Machine Learning (1465)

Published on in Vol 21, No 4 (2019): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12286, first published .
Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature

Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature

Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature

Authors of this article:

Andreas K Triantafyllidis1, 2 Author Orcid Image ;   Athanasios Tsanas3, 4 Author Orcid Image
Article Authors Cited by (158) Tweetations (72) Metrics

Journals

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  114. Ni Y, Lu Y, Jing F, Wang Q, Xie Y, He X, Wu D, Tan R, Tucker J, Yan X, Ong J, Zhang Q, Jiang H, Dai W, Huang L, Mei W, Zhou Y, Tang W. A Machine Learning Model for Identifying Sexual Health Influencers to Promote the Secondary Distribution of HIV Self-Testing Among Gay, Bisexual, and Other Men Who Have Sex With Men in China: Quasi-Experimental Study. JMIR Public Health and Surveillance 2024;10:e50656 View
  115. Sinaci A, Gencturk M, Alvarez-Romero C, Laleci Erturkmen G, Martinez-Garcia A, Escalona-Cuaresma M, Parra-Calderon C. Privacy-preserving federated machine learning on FAIR health data: A real-world application. Computational and Structural Biotechnology Journal 2024;24:136 View
  116. Ciftci R, Secgin Y, Oner Z, Toy S, Oner S. Age Estimation Using Machine Learning Algorithms with Parameters Obtained from X-ray Images of the Calcaneus. Nigerian Journal of Clinical Practice 2024;27(2):209 View
  117. Nadendla H, Etha P, Chowriappa P. Overcoming Confounding Bias in Causal Discovery Using Minimum Redundancy and Maximum Relevancy Constraint. IEEE Access 2024;12:33057 View
  118. Grijalvo M, Ordieres-Meré J, Villalba-Díez J, Aladro-Benito Y, Martín-Ávila G, Simon-Hurtado A, Vivaracho-Pascual C. Sufficiency for PSS tracking gait disorders in multiple sclerosis: A managerial perspective. Heliyon 2024;10(9):e30001 View
  119. Li J, Wang Z, Wang T. Machine-learning prediction of a novel diagnostic model using mitochondria-related genes for patients with bladder cancer. Scientific Reports 2024;14(1) View
  120. Baird A, Xia Y. Precision Digital Health. Business & Information Systems Engineering 2024;66(3):261 View
  121. Tsanas A, Triantafyllidis A, Tsiknakis M. Guest Editorial Pervasive Computing in Healthcare. IEEE Journal of Biomedical and Health Informatics 2024;28(5):2459 View
  122. Bucher A, Blazek E, Symons C. How are Machine Learning and Artificial Intelligence Used in Digital Behavior Change Interventions? A Scoping Review. Mayo Clinic Proceedings: Digital Health 2024;2(3):375 View
  123. Lundin R, Falcao V, Kannangara S, Eakin C, Abdar M, O'Neill J, Khosravi A, Eyre H, Nahavandi S, Loo C, Berk M. Machine Learning in Electroconvulsive Therapy. The Journal of ECT 2024 View
  124. Maher C, Dankiw K, Singh B, Bogomolova S, Curtis R. In-Home Evaluation of the Neo Care Artificial Intelligence Sound-Based Fall Detection System. Future Internet 2024;16(6):197 View
  125. Bader M, Abdelwanis M, Maalouf M, Jelinek H. Detecting depression severity using weighted random forest and oxidative stress biomarkers. Scientific Reports 2024;14(1) View
  126. Kuo Z, Chen K, Tseng Y. MoCab: A framework for the deployment of machine learning models across health information systems. Computer Methods and Programs in Biomedicine 2024;255:108336 View
  127. Iyawa G, Henton S, Maltinsky W, Casson A, Taylor A, Lake D, Medina-Lombardero S, Saleh M, Crichton M. Digital technologies for bowel management: A scoping review. Procedia Computer Science 2024;239:1745 View
  128. Danilov S, Matveev G, Babenko A, Shlyakhto E. Model for Predicting the Effect of Sibutramine Therapy in Obesity. Journal of Personalized Medicine 2024;14(8):811 View
  129. Irandoust K, Parsakia K, Estifa A, Zoormand G, Knechtle B, Rosemann T, Weiss K, Taheri M. Predicting and comparing the long-term impact of lifestyle interventions on individuals with eating disorders in active population: a machine learning evaluation. Frontiers in Nutrition 2024;11 View
  130. Mahfouz M, Mahfouz Y, Harmouche-Karaki M, Matta J, Younes H, Helou K, Finan R, Abi-Tayeh G, Meslimani M, Moussa G, Chahrour N, Osseiran C, Skaiki F, Narbonne J. Utilizing machine learning to classify persistent organic pollutants in the serum of pregnant women: a predictive modeling approach. Environmental Science and Pollution Research 2024;31(40):52980 View
  131. Aguilera A, Arévalo Avalos M, Xu J, Chakraborty B, Figueroa C, Garcia F, Rosales K, Hernandez-Ramos R, Karr C, Williams J, Ochoa-Frongia L, Sarkar U, Yom-Tov E, Lyles C. Effectiveness of a Digital Health Intervention Leveraging Reinforcement Learning: Results From the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation (DIAMANTE) Randomized Clinical Trial. Journal of Medical Internet Research 2024;26:e60834 View
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Books/Policy Documents

  1. Kubassova O, Shaikh F, Melus C, Mahler M. Precision Medicine and Artificial Intelligence. View
  2. Joel L, Doorsamy W, Paul B. Enhanced Telemedicine and e-Health. View
  3. Saini J, Dutta M, Marques G. Internet of Things for Indoor Air Quality Monitoring. View
  4. Kriksciuniene D, Sakalauskas V, Ognjanović I, Šendelj R. Intelligent Systems for Sustainable Person-Centered Healthcare. View
  5. Awotunde J, Chakraborty C, AbdulRaheem M, Jimoh R, Oladipo I, Bhoi A. Implementation of Smart Healthcare Systems using AI, IoT, and Blockchain. View
  6. Sakly H, Said M, Seekins J, Tagina M. Multidisciplinarity and Interdisciplinarity in Health. View
  7. Sulaiman M, Håkansson A, Karlsen R. ICT for Health, Accessibility and Wellbeing. View
  8. Schmitter-Edgecombe M, Luna C, Cook D. Positive Neuropsychology. View
  9. Miller S, Moos W, Munk B, Munk S, Hart C, Spellmeyer D. Managing the Drug Discovery Process. View
  10. Poonam , Batra N. Advanced Network Technologies and Intelligent Computing. View
  11. Erskine J, Fauquet-Alekhine P. The Palgrave Handbook of Occupational Stress. View
  12. Sestino A, D’Angelo A. Personalized Medicine Meets Artificial Intelligence. View
  13. Vamsi T, Shankar K, Karthik G, Puruvi M, Chanti B. Accelerating Discoveries in Data Science and Artificial Intelligence I. View