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Published on 10.10.17 in Vol 19, No 10 (2017): October

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

Works citing "Encouraging Physical Activity in Patients With Diabetes: Intervention Using a Reinforcement Learning System"

Elad Yom-Tov, Guy Feraru, Mark Kozdoba, Shie Mannor, Moshe Tennenholtz, Irit Hochberg

J Med Internet Res 2017 (Oct 10); 19(10):e338 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.7994):

(note that this is only a small subset of citations)

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  31. Figueroa CA, Aguilera A, Chakraborty B, Modiri A, Aggarwal J, Deliu N, Sarkar U, Jay Williams J, Lyles CR. Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions. Journal of the American Medical Informatics Association 2021;28(6):1225
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  32. Bharadwaj HK, Agarwal A, Chamola V, Lakkaniga NR, Hassija V, Guizani M, Sikdar B. A Review on the Role of Machine Learning in Enabling IoT Based Healthcare Applications. IEEE Access 2021;9:38859
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  33. Esefeld K, Kress S, Behrens M, Zimmer P, Stumvoll M, Thurm U, Gehr B, Brinkmann C, Halle M. Diabetes, Sport und Bewegung. Der Diabetologe 2021;17(3):330
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  34. De Chiara F, Ferret-Miñana A, Ramón-Azcón J. The Synergy between Organ-on-a-Chip and Artificial Intelligence for the Study of NAFLD: From Basic Science to Clinical Research. Biomedicines 2021;9(3):248
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  35. Steele R, Hillsgrove T, Khoshavi N, Jaimes LG. A survey of cyber-physical system implementations of real-time personalized interventions. Journal of Ambient Intelligence and Humanized Computing 2022;13(5):2325
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  38. Flores AM, Demsas F, Leeper NJ, Ross EG. Leveraging Machine Learning and Artificial Intelligence to Improve Peripheral Artery Disease Detection, Treatment, and Outcomes. Circulation Research 2021;128(12):1833
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  39. Nibbeling N, Simons M, Sporrel K, Deutekom M. A Focus Group Study Among Inactive Adults Regarding the Perceptions of a Theory-Based Physical Activity App. Frontiers in Public Health 2021;9
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  42. Sun X, Bee YM, Lam SW, Liu Z, Zhao W, Chia SY, Abdul Kadir H, Wu JT, Ang BY, Liu N, Lei Z, Xu Z, Zhao T, Hu G, Xie G. Effective Treatment Recommendations for Type 2 Diabetes Management Using Reinforcement Learning: Treatment Recommendation Model Development and Validation. Journal of Medical Internet Research 2021;23(7):e27858
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  43. Esefeld K, Kress S, Behrens M, Zimmer P, Stumvoll M, Thurm U, Gehr B, Brinkmann C, Halle M. Diabetes, Sport und Bewegung. Diabetologie und Stoffwechsel 2021;16(S 02):S299
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  44. Joachim S, Forkan ARM, Jayaraman PP, Morshed A, Wickramasinghe N. A Nudge-Inspired AI-Driven Health Platform for Self-Management of Diabetes. Sensors 2022;22(12):4620
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  45. Honka AM, Nieminen H, Simila H, Kaartinen J, Gils MV. A Comprehensive User Modeling Framework and a Recommender System for Personalizing Well-Being Related Behavior Change Interventions: Development and Evaluation. IEEE Access 2022;10:116766
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  46. Chong MS, Sit JWH, Karthikesu K, Chair SY. Effectiveness of technology-assisted cardiac rehabilitation: A systematic review and meta-analysis. International Journal of Nursing Studies 2021;124:104087
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  47. Esefeld K, Kress S, Behrens M, Zimmer P, Stumvoll M, Thurm U, Gehr B, Halle M, Brinkmann C. Diabetes, Sport und Bewegung. Diabetologie und Stoffwechsel 2022;17(S 02):S301
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  48. Trella AL, Zhang KW, Nahum-Shani I, Shetty V, Doshi-Velez F, Murphy SA. Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines. Algorithms 2022;15(8):255
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  49. Yu C, Liu J, Nemati S, Yin G. Reinforcement Learning in Healthcare: A Survey. ACM Computing Surveys 2023;55(1):1
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  50. Lim YS, Ho B, Goh Y. Effectiveness of game‐based exercise interventions on modifiable cardiovascular risk factors of individuals with type two diabetes mellitus: A systematic review and meta‐analysis. Worldviews on Evidence-Based Nursing 2023;20(4):377
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  51. Esefeld K, Kress S, Behrens M, Zimmer P, Stumvoll M, Thurm U, Gehr B, Halle M, Brinkmann C. Diabetes, Sports and Exercise. Experimental and Clinical Endocrinology & Diabetes 2023;131(01/02):51
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  52. Makroum MA, Adda M, Bouzouane A, Ibrahim H. Machine Learning and Smart Devices for Diabetes Management: Systematic Review. Sensors 2022;22(5):1843
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  53. Michaelsen MM, Esch T. Functional Mechanisms of Health Behavior Change Techniques: A Conceptual Review. Frontiers in Psychology 2022;13
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  54. Wang S, Zhang C, Kröse B, van Hoof H. Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator. Journal of Medical Systems 2021;45(12)
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  55. Daryabeygi-Khotbehsara R, Shariful Islam SM, Dunstan D, McVicar J, Abdelrazek M, Maddison R. Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review. Journal of Medical Internet Research 2021;23(9):e26315
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  56. Lauffenburger JC, Yom-Tov E, Keller PA, McDonnell ME, Bessette LG, Fontanet CP, Sears ES, Kim E, Hanken K, Buckley JJ, Barlev RA, Haff N, Choudhry NK. REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial. BMJ Open 2021;11(12):e052091
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  57. Bogina V, Kuflik T, Jannach D, Bielikova M, Kompan M, Trattner C. Considering temporal aspects in recommender systems: a survey. User Modeling and User-Adapted Interaction 2023;33(1):81
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  58. Vrátná E, Husáková J, Jarošíková R, Dubský M, Wosková V, Bém R, Jirkovská A, Králová K, Pyšková B, Lánská V, Fejfarová V. Effects of a 12-Week Interventional Exercise Programme on Muscle Strength, Mobility and Fitness in Patients With Diabetic Foot in Remission: Results From BIONEDIAN Randomised Controlled Trial. Frontiers in Endocrinology 2022;13
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  59. Di S, Petch J, Gerstein HC, Zhu R, Sherifali D. Optimizing Health Coaching for Patients With Type 2 Diabetes Using Machine Learning: Model Development and Validation Study. JMIR Formative Research 2022;6(9):e37838
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.7994):

  1. Lamba D, Hsu WH, Alsadhan M. Machine Learning, Big Data, and IoT for Medical Informatics. 2021. :1
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  2. Qian X, Zhu Z, Wang K, Zhou Z. Advances in Intelligent Automation and Soft Computing. 2022. Chapter 136:1180
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  3. Ozkaynak M, Skiba D. Nursing Informatics. 2022. Chapter 19:267
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  4. . Handbook of Computational Social Science for Policy. 2023. Chapter 15:279
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  5. de Bruijn G, Liu S, Rhodes R. The International Encyclopedia of Health Communication. 2022. :1
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  6. El rhatassi FE, El Ghali B, Daoudi N. Proceedings of the 6th International Conference on Big Data and Internet of Things. 2023. Chapter 37:435
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