Published on in Vol 2, No 2 (2017): Jul-Dec

A Fully Automated Conversational Artificial Intelligence for Weight Loss: Longitudinal Observational Study Among Overweight and Obese Adults

A Fully Automated Conversational Artificial Intelligence for Weight Loss: Longitudinal Observational Study Among Overweight and Obese Adults

A Fully Automated Conversational Artificial Intelligence for Weight Loss: Longitudinal Observational Study Among Overweight and Obese Adults

Authors of this article:

Natalie Stein 1 Author Orcid Image ;   Kevin Brooks 2 Author Orcid Image

Journals

  1. Mandigout S, Perrochon A, Fernandez L, Rezzoug N, Encelle B, Kanellos I, Ricard D, Bouet M, Shneider M, Buffat S. A Multidimensional Data Acquisition as a Preliminary Step to the Secondary Prevention of the Loss of Autonomy for Patients with Traumatic Injury and Stroke: An AMISIA Pilot Study. IRBM 2020;41(6):316 View
  2. Maeda E, Miyata A, Boivin J, Nomura K, Kumazawa Y, Shirasawa H, Saito H, Terada Y. Promoting fertility awareness and preconception health using a chatbot: a randomized controlled trial. Reproductive BioMedicine Online 2020 View
  3. Issom D, Henriksen A, Woldaregay A, Rochat J, Lovis C, Hartvigsen G. Factors Influencing Motivation and Engagement in Mobile Health Among Patients With Sickle Cell Disease in Low-Prevalence, High-Income Countries: Qualitative Exploration of Patient Requirements. JMIR Human Factors 2020;7(1):e14599 View
  4. Javaid M, Haleem A, Khan I, Vaishya R, Vaish A. Extending capabilities of artificial intelligence for decision-making and healthcare education. Apollo Medicine 2020;17(1):53 View
  5. Lin S, Mahoney M, Sinsky C. Ten Ways Artificial Intelligence Will Transform Primary Care. Journal of General Internal Medicine 2019;34(8):1626 View
  6. Kaufman N, Ferrin C, Sugrue D. Using Digital Health Technology to Prevent and Treat Diabetes. Diabetes Technology & Therapeutics 2019;21(S1):S-79 View
  7. Maher C, Davis C, Curtis R, Short C, Murphy K. A Physical Activity and Diet Program Delivered by Artificially Intelligent Virtual Health Coach: Proof-of-Concept Study. JMIR mHealth and uHealth 2020;8(7):e17558 View
  8. Arena R, Ozemek C, Laddu D, Campbell T, Rouleau C, Standley R, Bond S, Abril E, Hills A, Lavie C. Applying Precision Medicine to Healthy Living for the Prevention and Treatment of Cardiovascular Disease. Current Problems in Cardiology 2018;43(12):448 View
  9. Turchioe M, Heitkemper E, Lor M, Burgermaster M, Mamykina L. Designing for engagement with self-monitoring: A user-centered approach with low-income, Latino adults with Type 2 Diabetes. International Journal of Medical Informatics 2019;130:103941 View
  10. Levine B, Close K, Gabbay R. Reviewing U.S. Connected Diabetes Care: The Newest Member of the Team. Diabetes Technology & Therapeutics 2020;22(1):1 View
  11. Ploug T, Holm S. The right to refuse diagnostics and treatment planning by artificial intelligence. Medicine, Health Care and Philosophy 2020;23(1):107 View
  12. Brar Prayaga R, Agrawal R, Nguyen B, Jeong E, Noble H, Paster A, Prayaga R. Impact of Social Determinants of Health and Demographics on Refill Requests by Medicare Patients Using a Conversational Artificial Intelligence Text Messaging Solution: Cross-Sectional Study. JMIR mHealth and uHealth 2019;7(11):e15771 View
  13. Muralidharan S, Ranjani H, Mohan Anjana R, Jena S, Tandon N, Gupta Y, Ambekar S, Koppikar V, Jagannathan N, Allender S, Mohan V. Engagement and Weight Loss: Results from the Mobile Health and Diabetes Trial. Diabetes Technology & Therapeutics 2019;21(9):507 View
  14. Zhang J, Oh Y, Lange P, Yu Z, Fukuoka Y. Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint. Journal of Medical Internet Research 2020;22(9):e22845 View
  15. Meyer R, Spittel S, Steinfurth L, Funke A, Kettemann D, Münch C, Meyer T, Maier A. Patient-Reported Outcome of Physical Therapy in Amyotrophic Lateral Sclerosis: Observational Online Study. JMIR Rehabilitation and Assistive Technologies 2018;5(2):e10099 View
  16. Song H. Clinical Psychology in the Age of in the new technology : focusing on the recent studies trends. The Korean Journal of Psychology: General 2019;38(4):549 View
  17. Bardus M, Hamadeh G, Hayek B, Al Kherfan R. A Self-Directed Mobile Intervention (WaznApp) to Promote Weight Control Among Employees at a Lebanese University: Protocol for a Feasibility Pilot Randomized Controlled Trial. JMIR Research Protocols 2018;7(5):e133 View
  18. Neborachko M, Pkhakadze A, Vlasenko I. Current trends of digital solutions for diabetes management. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 2019;13(5):2997 View
  19. Tudor Car L, Dhinagaran D, Kyaw B, Kowatsch T, Joty S, Theng Y, Atun R. Conversational Agents in Health Care: Scoping Review and Conceptual Analysis. Journal of Medical Internet Research 2020;22(8):e17158 View
  20. Issom D, Hardy-Dessources M, Romana M, Hartvigsen G, Lovis C. Toward a Conversational Agent to Support the Self-Management of Adults and Young Adults With Sickle Cell Disease: Usability and Usefulness Study. Frontiers in Digital Health 2021;3 View
  21. Falter M, Scherrenberg M, Dendale P. Digital Health in Cardiac Rehabilitation and Secondary Prevention: A Search for the Ideal Tool. Sensors 2020;21(1):12 View
  22. Tsakanikas V, Gatsios D, Dimopoulos D, Pardalis A, Pavlou M, Liston M, Fotiadis D. Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching System. Frontiers in Digital Health 2020;2 View
  23. Rafferty A, Hall R, Johnston C. A Novel Mobile App (Heali) for Disease Treatment in Participants With Irritable Bowel Syndrome: Randomized Controlled Pilot Trial. Journal of Medical Internet Research 2021;23(3):e24134 View
  24. Liu S, Ko Q, Heng K, Ngiam K, Feng M. Healthcare Transformation in Singapore With Artificial Intelligence. Frontiers in Digital Health 2020;2 View
  25. Morgenstern J, Rosella L, Daley M, Goel V, Schünemann H, Piggott T. “AI’s gonna have an impact on everything in society, so it has to have an impact on public health”: a fundamental qualitative descriptive study of the implications of artificial intelligence for public health. BMC Public Health 2021;21(1) View
  26. Davis C, Murphy K, Curtis R, Maher C. A Process Evaluation Examining the Performance, Adherence, and Acceptability of a Physical Activity and Diet Artificial Intelligence Virtual Health Assistant. International Journal of Environmental Research and Public Health 2020;17(23):9137 View
  27. Snir M, Nazareth S, Simmons E, Hayward L, Ashcraft K, Bristow S, Esplin E, Aradhya S. Democratizing genomics: Leveraging software to make genetics an integral part of routine care. American Journal of Medical Genetics Part C: Seminars in Medical Genetics 2021;187(1):14 View
  28. Chew H, Ang W, Lau Y. The potential of artificial intelligence in enhancing adult weight loss: a scoping review. Public Health Nutrition 2021;24(8):1993 View
  29. Lopez-Picazo J, Vidal-Abarca I, Beteta D, López-Ibáñez M, García-Vázquez E. Impact of the COVID-19 Pandemic on the Hospital: Inpatient’s Perceived Quality in Spain. Journal of Patient Experience 2021;8:237437352199862 View
  30. Thomas Craig K, Morgan L, Chen C, Michie S, Fusco N, Snowdon J, Scheufele E, Gagliardi T, Sill S. Systematic review of context-aware digital behavior change interventions to improve health. Translational Behavioral Medicine 2021;11(5):1037 View
  31. Nyrup R. From General Principles to Procedural Values: Responsible Digital Health Meets Public Health Ethics. Frontiers in Digital Health 2021;3 View

Books/Policy Documents

  1. Cho P, Singh K, Dunn J. Artificial Intelligence in Medicine. View
  2. Belciug S, Gorunescu F. Intelligent Decision Support Systems—A Journey to Smarter Healthcare. View