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Citing this Article

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Published on 01.11.17 in Vol 2, No 2 (2017): Jul-Dec

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

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

Natalie Stein, Kevin Brooks

JMIR Diabetes 2017 (Nov 01); 2(2):e28 

According to Crossref, the following articles are citing this article (DOI 10.2196/diabetes.8590):

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

  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
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  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;41(6):1133
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  3. Issom D, Henriksen A, Woldaregay AZ, 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
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  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
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  7. Maher CA, Davis CR, Curtis RG, Short CE, Murphy KJ. 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
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  8. Arena R, Ozemek C, Laddu D, Campbell T, Rouleau CR, Standley R, Bond S, Abril EP, Hills AP, Lavie CJ. Applying Precision Medicine to Healthy Living for the Prevention and Treatment of Cardiovascular Disease. Current Problems in Cardiology 2018;43(12):448
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  9. Turchioe MR, Heitkemper EM, 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
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  10. Levine BJ, Close KL, Gabbay RA. Reviewing U.S. Connected Diabetes Care: The Newest Member of the Team. Diabetes Technology & Therapeutics 2020;22(1):1
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  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
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  12. Brar Prayaga R, Agrawal R, Nguyen B, Jeong EW, Noble HK, Paster A, Prayaga RS. 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
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  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
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  14. Zhang J, Oh YJ, 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
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  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
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  16. . 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
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  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
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  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
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  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
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  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
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  22. Tsakanikas VD, Gatsios D, Dimopoulos D, Pardalis A, Pavlou M, Liston MB, Fotiadis DI. 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
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  23. Rafferty AJ, Hall R, Johnston CS. 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
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  24. Liu S, Ko QS, Heng KQA, Ngiam KY, Feng M. Healthcare Transformation in Singapore With Artificial Intelligence. Frontiers in Digital Health 2020;2
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  25. Morgenstern JD, Rosella LC, Daley MJ, Goel V, Schünemann HJ, 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)
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  26. Davis CR, Murphy KJ, Curtis RG, Maher CA. 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
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  27. Snir M, Nazareth S, Simmons E, Hayward L, Ashcraft K, Bristow SL, Esplin ED, 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
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  28. Chew HSJ, Ang WHD, Lau Y. The potential of artificial intelligence in enhancing adult weight loss: a scoping review. Public Health Nutrition 2021;24(8):1993
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  29. Lopez-Picazo JJ, 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
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  30. Thomas Craig KJ, Morgan LC, Chen C, Michie S, Fusco N, Snowdon JL, 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
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  31. . From General Principles to Procedural Values: Responsible Digital Health Meets Public Health Ethics. Frontiers in Digital Health 2021;3
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  32. Petroni ML, Brodosi L, Marchignoli F, Sasdelli AS, Caraceni P, Marchesini G, Ravaioli F. Nutrition in Patients with Type 2 Diabetes: Present Knowledge and Remaining Challenges. Nutrients 2021;13(8):2748
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  33. Zhou X, Chen L, Liu H. Applications of Machine Learning Models to Predict and Prevent Obesity: A Mini-Review. Frontiers in Nutrition 2022;9
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  34. Goh YS, Ow Yong JQY, Chee BQH, Kuek JHL, Ho CSH. Machine Learning in Health Promotion and Behavioral Change: Scoping Review. Journal of Medical Internet Research 2022;24(6):e35831
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  35. . The Use of Artificial Intelligence–Based Conversational Agents (Chatbots) for Weight Loss: Scoping Review and Practical Recommendations. JMIR Medical Informatics 2022;10(4):e32578
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  36. Peng X, Tang L. Exploring the Characteristics of Physical Exercise in Students and the Path of Health Education. Frontiers in Psychology 2021;12
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  37. Job JR, Eakin EG, Reeves MM, Fjeldsoe BS. Evaluation of the Healthy Living after Cancer text message-delivered, extended contact intervention using the RE-AIM framework. BMC Cancer 2021;21(1)
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  38. Lyzwinski LN, Elgendi M, Menon C. Conversational Agents and Avatars for Cardiometabolic Risk Factors and Lifestyle-Related Behaviors: Scoping Review. JMIR mHealth and uHealth 2023;11:e39649
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  39. Schmidlen T, Jones CL, Campbell‐Salome G, McCormick CZ, Vanenkevort E, Sturm AC. Use of a chatbot to increase uptake of cascade genetic testing. Journal of Genetic Counseling 2022;31(5):1219
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  40. Graham SA, Pitter V, Hori JH, Stein N, Branch OH. Weight loss in a digital app-based diabetes prevention program powered by artificial intelligence. DIGITAL HEALTH 2022;8:205520762211306
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  41. Ta-Johnson VP, Boatfield C, Wang X, DeCero E, Krupica IC, Rasof SD, Motzer A, Pedryc WM. Assessing the Topics and Motivating Factors Behind Human-Social Chatbot Interactions: Thematic Analysis of User Experiences. JMIR Human Factors 2022;9(4):e38876
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  42. op den Akker H, Cabrita M, Pnevmatikakis A. Digital Therapeutics: Virtual Coaching Powered by Artificial Intelligence on Real-World Data. Frontiers in Computer Science 2021;3
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  43. Cranefield J, Winikoff M, Chiu Y, Li Y, Doyle C, Richter A. Partnering with AI: the case of digital productivity assistants. Journal of the Royal Society of New Zealand 2023;53(1):95
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  44. Salas-Groves E, Galyean S, Alcorn M, Childress A. Behavior Change Effectiveness Using Nutrition Apps in People With Chronic Diseases: Scoping Review. JMIR mHealth and uHealth 2023;11:e41235
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  45. Fisher S, Rosella LC. Priorities for successful use of artificial intelligence by public health organizations: a literature review. BMC Public Health 2022;22(1)
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  46. Bombard Y, Ginsburg GS, Sturm AC, Zhou AY, Lemke AA. Digital health-enabled genomics: Opportunities and challenges. The American Journal of Human Genetics 2022;109(7):1190
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  47. Chu Y, Huang R, Chen TT, Lin W, Tang JT, Lin C, Huang C, Lin C, Chen J, Kurtz-Rossi S, Sørensen K. Effect of health literacy and shared decision-making on choice of weight-loss plan among overweight or obese participants receiving a prototype artificial intelligence robot intervention facilitating weight-loss management decisions. DIGITAL HEALTH 2022;8:205520762211363
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  48. Szinay D, Forbes CC, Busse H, DeSmet A, Smit ES, König LM. Is the uptake, engagement, and effectiveness of exclusively mobile interventions for the promotion of weight‐related behaviors equal for all? A systematic review. Obesity Reviews 2023;24(3)
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  49. Amagai S, Pila S, Kaat AJ, Nowinski CJ, Gershon RC. Challenges in Participant Engagement and Retention Using Mobile Health Apps: Literature Review. Journal of Medical Internet Research 2022;24(4):e35120
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  50. Budler LC, Gosak L, Stiglic G. Review of artificial intelligence‐based question‐answering systems in healthcare. WIREs Data Mining and Knowledge Discovery 2023;13(2)
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  51. Luca S, Clausen M, Shaw A, Lee W, Krishnapillai S, Adi-Wauran E, Faghfoury H, Costain G, Jobling R, Aronson M, Liston E, Silver J, Shuman C, Chad L, Hayeems RZ, Bombard Y, Bernier F, Brudno M, Carroll JC, Cohn R, Dhalla I, Friedman J, Hewson S, Jamieson T, Kodida R, Laberge A, Lerner-Ellis J, Mamdani M, Marshall CR, Osmond M, Pham Q, Reble E, Rudzicz F, Seto E, Shastri-Estrada S, Smith M, Thorpe K, Ungar WJ. Finding the sweet spot: a qualitative study exploring patients’ acceptability of chatbots in genetic service delivery. Human Genetics 2023;142(3):321
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  52. Maier A, Gaudlitz M, Grehl T, Weyen U, Steinbach R, Grosskreutz J, Rödiger A, Koch JC, Lengenfeld T, Weydt P, Günther R, Wolf J, Baum P, Metelmann M, Dorst J, Ludolph AC, Kettemann D, Norden J, Koc RY, Walter B, Hildebrandt B, Münch C, Meyer T, Spittel S. Use and subjective experience of the impact of motor-assisted movement exercisers in people with amyotrophic lateral sclerosis: a multicenter observational study. Scientific Reports 2022;12(1)
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  53. Fjeldsoe BS, Goode AD, Job J, Eakin EG, Spilsbury KL, Winkler E. Dose and engagement during an extended contact physical activity and dietary behavior change intervention delivered via tailored text messaging: exploring relationships with behavioral outcomes. International Journal of Behavioral Nutrition and Physical Activity 2021;18(1)
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  54. König LM, Van Emmenis M, Nurmi J, Kassavou A, Sutton S. Characteristics of smartphone-based dietary assessment tools: a systematic review. Health Psychology Review 2022;16(4):526
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  55. Antoun J, Itani H, Alarab N, Elsehmawy A. The Effectiveness of Combining Nonmobile Interventions With the Use of Smartphone Apps With Various Features for Weight Loss: Systematic Review and Meta-analysis. JMIR mHealth and uHealth 2022;10(4):e35479
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  56. Chew HSJ, Gao Y, Shabbir A, Lim SL, Geetha K, Kim G, Chong CS, Lomanto D, So BYJ. Personal motivation, self-regulation barriers and strategies for weight loss in people with overweight and obesity: a thematic framework analysis. Public Health Nutrition 2022;25(9):2426
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  57. Kyung N, Kwon HE. Rationally trust, but emotionally? The roles of cognitive and affective trust in laypeople's acceptance of AI for preventive care operations. Production and Operations Management 2022;
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  58. Kazemi SS, Tavafian SS, Montazeri A. The Social Media Intervention For Lower Back Pain Education Study (SMILE): A Protocol For A Randomized Trial To Reduce Occupational Low Back Pain In Nursing Professionals. International Journal of Musculoskeletal Pain Prevention 2019;4(3):211
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  59. Aggarwal A, Tam CC, Wu D, Li X, Qiao S. Artificial Intelligence–Based Chatbots for Promoting Health Behavioral Changes: Systematic Review. Journal of Medical Internet Research 2023;25:e40789
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  60. Ollier J, Nißen M, von Wangenheim F. The Terms of “You(s)”: How the Term of Address Used by Conversational Agents Influences User Evaluations in French and German Linguaculture. Frontiers in Public Health 2022;9
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  61. Brůha P, Mouček R, Salamon J, Vacek V. Workflow for health-related and brain data lifecycle. Frontiers in Digital Health 2022;4
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  63. Chew HSJ, Achananuparp P. Perceptions and Needs of Artificial Intelligence in Health Care to Increase Adoption: Scoping Review. Journal of Medical Internet Research 2022;24(1):e32939
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  65. Dwivedi YK, Kshetri N, Hughes L, Slade EL, Jeyaraj A, Kar AK, Baabdullah AM, Koohang A, Raghavan V, Ahuja M, Albanna H, Albashrawi MA, Al-Busaidi AS, Balakrishnan J, Barlette Y, Basu S, Bose I, Brooks L, Buhalis D, Carter L, Chowdhury S, Crick T, Cunningham SW, Davies GH, Davison RM, Dé R, Dennehy D, Duan Y, Dubey R, Dwivedi R, Edwards JS, Flavián C, Gauld R, Grover V, Hu M, Janssen M, Jones P, Junglas I, Khorana S, Kraus S, Larsen KR, Latreille P, Laumer S, Malik FT, Mardani A, Mariani M, Mithas S, Mogaji E, Nord JH, O’Connor S, Okumus F, Pagani M, Pandey N, Papagiannidis S, Pappas IO, Pathak N, Pries-Heje J, Raman R, Rana NP, Rehm S, Ribeiro-Navarrete S, Richter A, Rowe F, Sarker S, Stahl BC, Tiwari MK, van der Aalst W, Venkatesh V, Viglia G, Wade M, Walton P, Wirtz J, Wright R. Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management 2023;71:102642
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  1. Cho PJ, Singh K, Dunn J. Artificial Intelligence in Medicine. 2021. :151
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  2. Belciug S, Gorunescu F. Intelligent Decision Support Systems—A Journey to Smarter Healthcare. 2020. Chapter 3:71
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  4. Ruiz RB, Velásquez JD. Artificial Intelligence and Machine Learning for Healthcare. 2023. Chapter 1:1
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