Published on in Vol 7, No 5 (2019): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9232, first published .
A Focused Review of Smartphone Diet-Tracking Apps: Usability, Functionality, Coherence With Behavior Change Theory, and Comparative Validity of Nutrient Intake and Energy Estimates

A Focused Review of Smartphone Diet-Tracking Apps: Usability, Functionality, Coherence With Behavior Change Theory, and Comparative Validity of Nutrient Intake and Energy Estimates

A Focused Review of Smartphone Diet-Tracking Apps: Usability, Functionality, Coherence With Behavior Change Theory, and Comparative Validity of Nutrient Intake and Energy Estimates

Journals

  1. Milne-Ives M, Lam C, De Cock C, Van Velthoven M, Meinert E. Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review. JMIR mHealth and uHealth 2020;8(3):e17046 View
  2. Milne-Ives M, Lam C, van Velthoven M, Meinert E. Mobile Fitness and Weight Management Apps: Protocol for a Quality Evaluation. JMIR Research Protocols 2020;9(9):e17685 View
  3. Picoraro J, Akabas S, LeLeiko N. Harmonizing Nutritional Therapies for Pediatric Inflammatory Bowel Disease. Journal of Pediatric Gastroenterology and Nutrition 2020;70(3):285 View
  4. McCaig D, Elliott M, Prnjak K, Walasek L, Meyer C. Engagement with MyFitnessPal in eating disorders: Qualitative insights from online forums. International Journal of Eating Disorders 2020;53(3):404 View
  5. Mandracchia F, Llauradó E, Tarro L, Valls R, Solà R. Mobile Phone Apps for Food Allergies or Intolerances in App Stores: Systematic Search and Quality Assessment Using the Mobile App Rating Scale (MARS). JMIR mHealth and uHealth 2020;8(9):e18339 View
  6. Milne-Ives M, Lam C, Van Velthoven M, Meinert E. Mobile Apps for Health Behavior Change: Protocol for a Systematic Review. JMIR Research Protocols 2020;9(1):e16931 View
  7. Khazen W, Jeanne J, Demaretz L, Schäfer F, Fagherazzi G. Rethinking the Use of Mobile Apps for Dietary Assessment in Medical Research. Journal of Medical Internet Research 2020;22(6):e15619 View
  8. Schäfer F, Faviez C, Voillot P, Foulquié P, Najm M, Jeanne J, Fagherazzi G, Schück S, Le Nevé B. Mapping and Modeling of Discussions Related to Gastrointestinal Discomfort in French-Speaking Online Forums: Results of a 15-Year Retrospective Infodemiology Study. Journal of Medical Internet Research 2020;22(11):e17247 View
  9. Tosi M, Radice D, Carioni G, Vecchiati T, Fiori F, Parpinel M, Gnagnarella P. Accuracy of applications to monitor food intake: Evaluation by comparison with 3-d food diary. Nutrition 2021;84:111018 View
  10. Rubin D, Rich Severin , Arena R, Bond S. Leveraging technology to move more and sit less. Progress in Cardiovascular Diseases 2021;64:55 View
  11. Shinozaki N, Murakami K. Evaluation of the Ability of Diet-Tracking Mobile Applications to Estimate Energy and Nutrient Intake in Japan. Nutrients 2020;12(11):3327 View
  12. Zugasti Murillo A. Applicability of innovation in clinical nutrition. Nutrición Hospitalaria 2021 View
  13. Mustafa N, Safii N, Jaffar A, Sani N, Mohamad M, Abd Rahman A, Mohd Sidik S. Malay Version of the mHealth App Usability Questionnaire (M-MAUQ): Translation, Adaptation, and Validation Study. JMIR mHealth and uHealth 2021;9(2):e24457 View
  14. 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
  15. Kolinsky N, Weare-Regales N, Lockey R. A Practical Approach to Assist Asthmatics to Lose Weight. The Journal of Allergy and Clinical Immunology: In Practice 2021;9(6):2245 View
  16. Morgenstern J, Rosella L, Costa A, de Souza R, Anderson L. Perspective: Big Data and Machine Learning Could Help Advance Nutritional Epidemiology. Advances in Nutrition 2021;12(3):621 View
  17. Turner-McGrievy G, Yang C, Monroe C, Pellegrini C, West D. Is Burden Always Bad? Emerging Low-Burden Approaches to Mobile Dietary Self-monitoring and the Role Burden Plays with Engagement. Journal of Technology in Behavioral Science 2021;6(3):447 View
  18. Srinivasan B, Finkelstein J, Erickson D, Mehta S. Point-of-Care Quantification of Serum Alpha-Fetoprotein for Screening Birth Defects in Resource-Limited Settings: Proof-of-Concept Study. JMIR Biomedical Engineering 2021;6(1):e23527 View
  19. Molina Recio G, Molina-Luque R, Romero-Saldaña M. The importance of knowing and listening to all those involved in the design and use of nutrition mobile apps. Getting to know the Great GApp. Nutrición Hospitalaria 2021 View
  20. Roux de Bézieux H, Bullard J, Kolterman O, Souza M, Perraudeau F. Medical Food Assessment Using a Smartphone App With Continuous Glucose Monitoring Sensors: Proof-of-Concept Study. JMIR Formative Research 2021;5(3):e20175 View
  21. McClung H, Raynor H, Volpe S, Dwyer J, Papoutsakis C. A Primer for the Evaluation and Integration of Dietary Intake and Physical Activity Digital Measurement Tools into Nutrition and Dietetics Practice. Journal of the Academy of Nutrition and Dietetics 2022;122(1):207 View
  22. Ocké M, Dinnissen C, Stafleu A, de Vries J, van Rossum C. Relative Validity of MijnEetmeter: A Food Diary App for Self-Monitoring of Dietary Intake. Nutrients 2021;13(4):1135 View
  23. Zečević M, Mijatović D, Kos Koklič M, Žabkar V, Gidaković P. User Perspectives of Diet-Tracking Apps: Reviews Content Analysis and Topic Modeling. Journal of Medical Internet Research 2021;23(4):e25160 View
  24. Ruf A, Koch E, Ebner-Priemer U, Knopf M, Reif A, Matura S. Studying Microtemporal, Within-Person Processes of Diet, Physical Activity, and Related Factors Using the APPetite-Mobile-App: Feasibility, Usability, and Validation Study. Journal of Medical Internet Research 2021;23(7):e25850 View
  25. Zhang L, Misir A, Boshuizen H, Ocké M. A Systematic Review and Meta-Analysis of Validation Studies Performed on Dietary Record Apps. Advances in Nutrition 2021;12(6):2321 View
  26. Wit R, Lucassen D, Beulen Y, Faessen J, Bos-de Vos M, van Dongen J, Feskens E, Wagemakers A, Brouwer-Brolsma E. Midwives’ Experiences with and Perspectives on Online (Nutritional) Counselling and mHealth Applications for Pregnant Women; an Explorative Qualitative Study. International Journal of Environmental Research and Public Health 2021;18(13):6733 View
  27. Chen Y, Ji M, Wu Y, Deng Y, Wu F, Lu Y. Individualized mobile health interventions for cardiovascular event prevention in patients with coronary heart disease: study protocol for the iCARE randomized controlled trial. BMC Cardiovascular Disorders 2021;21(1) View
  28. Lucassen D, Lasschuijt M, Camps G, Van Loo E, Fischer A, de Vries R, Haarman J, Simons M, de Vet E, Bos-de Vos M, Pan S, Ren X, de Graaf K, Lu Y, Feskens E, Brouwer-Brolsma E. Short and Long-Term Innovations on Dietary Behavior Assessment and Coaching: Present Efforts and Vision of the Pride and Prejudice Consortium. International Journal of Environmental Research and Public Health 2021;18(15):7877 View
  29. Richardson K, Cota Aguirre G, Weiss R, Cinar A, Liao Y, Marano K, Bedoya A, Schembre S. Abbreviated Dietary Self-monitoring for Type 2 Diabetes Management: Mixed Methods Feasibility Study. JMIR Diabetes 2021;6(3):e28930 View
  30. Eisenhauer C, Brito F, Kupzyk K, Yoder A, Almeida F, Beller R, Miller J, Hageman P. Mobile health assisted self-monitoring is acceptable for supporting weight loss in rural men: a pragmatic randomized controlled feasibility trial. BMC Public Health 2021;21(1) View
  31. Hauptmann H, Leipold N, Madenach M, Wintergerst M, Lurz M, Groh G, Böhm M, Gedrich K, Krcmar H. Effects and challenges of using a nutrition assistance system: results of a long-term mixed-method study. User Modeling and User-Adapted Interaction 2022;32(5):923 View
  32. Samad S, Ahmed F, Naher S, Kabir M, Das A, Amin S, Islam S. Smartphone apps for tracking food consumption and recommendations: Evaluating artificial intelligence-based functionalities, features and quality of current apps. Intelligent Systems with Applications 2022;15:200103 View
  33. Pfammatter A, Hughes B, Tucker B, Whitmore H, Spring B, Tasali E. The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed. Journal of Medical Internet Research 2022;24(12):e39489 View
  34. Threapleton D, Beer S, Foley D, Gibson L, Trevillion S, Burke D, Wheatstone P, Gath J, Hex N, Setters J, Greenwood D, Cade J. Usability of myfood24 Healthcare and Mathematical Diet Optimisation in Clinical Populations: A Pilot Feasibility Randomised Controlled Trial. Nutrients 2022;14(9):1768 View
  35. Falter M, Scherrenberg M, Dendale P. Digital health in de cardiovasculaire preventie en revalidatie. Tijdschrift voor Geneeskunde 2022 View
  36. Zhang L, Wu J, Yang J, Chen S, Liu J, Zhang P, Chu J, Luo C, Parameshachari B. Development and Application Evaluation of a Nursing Simulation Teaching Information System Based on Hospital Information Systems. International Journal of Clinical Practice 2023;2023:1 View
  37. Standen E, Rothman A. Capitalizing on the potential of mobile health applications as behavioral interventions: A research agenda for calorie‐tracking and activity‐tracking applications. Social and Personality Psychology Compass 2023;17(3) View
  38. Saarikko J, Axelin A, Huvinen E, Rahmani A, Azimi I, Pasanen M, Niela-Vilén H, Stortz J. Supporting lifestyle change in obese pregnant mothers through the wearable internet-of-things (SLIM) -intervention for overweight pregnant women: Study protocol for a quasi-experimental trial. PLOS ONE 2023;18(1):e0279696 View
  39. Pape M, Färber T, Seiferth C, Roth T, Schroeder S, Wolstein J, Herpertz S, Steins-Loeber S. A Tailored Gender-Sensitive mHealth Weight Loss Intervention (I-GENDO): Development and Process Evaluation. JMIR Formative Research 2022;6(10):e38480 View
  40. McVay M, Cooper K, Donahue M, Seoane M, Shah N, Webb F, Perri M, Jake‐Schoffman D. Engaging primary care patients with existing online tools for weight loss: A pilot trial. Obesity Science & Practice 2022;8(5):569 View
  41. An R, Perez-Cruet J, Wang J. We got nuts! use deep neural networks to classify images of common edible nuts. Nutrition and Health 2022:026010602211139 View
  42. Faessen J, Lucassen D, Buso M, Camps G, Feskens E, Brouwer-Brolsma E. Eating for 2: A Systematic Review of Dutch App Stores for Apps Promoting a Healthy Diet during Pregnancy. Current Developments in Nutrition 2022;6(6):nzac087 View
  43. Frick M, Neu L, Liebhaber N, Sperner-Unterweger B, Stötter J, Keller L, Hüfner K. Why Do We Harm the Environment or Our Personal Health despite Better Knowledge? The Knowledge Action Gap in Healthy and Climate-Friendly Behavior. Sustainability 2021;13(23):13361 View
  44. Hyzy M, Bond R, Mulvenna M, Bai L, Dix A, Leigh S, Hunt S. System Usability Scale Benchmarking for Digital Health Apps: Meta-analysis. JMIR mHealth and uHealth 2022;10(8):e37290 View
  45. Scott J, Vijayakumar A, Woodside J, Neville C. Feasibility of wearable camera use to improve the accuracy of dietary assessment among adults. Journal of Nutritional Science 2022;11 View
  46. Mistura L, Comendador Azcarraga F, D’Addezio L, Martone D, Turrini A. An Italian Case Study for Assessing Nutrient Intake through Nutrition-Related Mobile Apps. Nutrients 2021;13(9):3073 View
  47. Siniarski A, Sobieraj P, Samel-Kowalik P, Sińska B, Milewska M, Bzikowska-Jura A. Nutrition-related mobile applications - Should they be used for dietary prevention and treatment of cardiovascular diseases?. Nutrition, Metabolism and Cardiovascular Diseases 2022;32(11):2505 View
  48. Chew H, Koh W, Ng J, Tan K. Sustainability of Weight Loss Through Smartphone Apps: Systematic Review and Meta-analysis on Anthropometric, Metabolic, and Dietary Outcomes. Journal of Medical Internet Research 2022;24(9):e40141 View
  49. Thornton L, Osman B, Champion K, Green O, Wescott A, Gardner L, Stewart C, Visontay R, Whife J, Parmenter B, Birrell L, Bryant Z, Chapman C, Lubans D, Slade T, Torous J, Teesson M, Van de Ven P. Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review. JMIR mHealth and uHealth 2022;10(2):e27337 View
  50. Montoye A, Vondrasek J, Neph S. Validation of the SmartPlate for detecting food weight and type. International Journal of Food Sciences and Nutrition 2023;74(1):22 View
  51. Kong N, Moy F, Ong S, Tahir G, Loo C. MyDietCam: Development and usability study of a food recognition integrated dietary monitoring smartphone application. DIGITAL HEALTH 2023;9:205520762211493 View
  52. Dufendach K, Navarro-Sainz A, Webster K. Usability of human-computer interaction in neonatal care. Seminars in Fetal and Neonatal Medicine 2022;27(5):101395 View
  53. Lorenzi L, Belo L, Frohlich D, Dourado V, Castro P, Gomes G. Factors related to the adoption and adherence of physical activity mobile applications by older people: a scoping review protocol. BMJ Open 2021;11(10):e052414 View
  54. MARCHANT E, MARCHANT N, HYLDAHL R, GIFFORD J, SMITH M, HANCOCK C. Skeletal Muscle Mitochondrial Function after a 100-km Ultramarathon: A Case Study in Monozygotic Twins. Medicine & Science in Sports & Exercise 2021;53(11):2363 View
  55. Lara-Breitinger K, Lynch M, Kopecky S. Nutrition Intervention in Cardiac Rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention 2021;41(6):383 View
  56. Austin D, May J, Andrade J, Nichols A. Exploring barriers, motivators and solutions to achieve a healthy lifestyle among undergraduate student nurses. British Journal of Nursing 2022;31(4):240 View
  57. Turrini A. Perspectives of Dietary Assessment in Human Health and Disease. Nutrients 2022;14(4):830 View
  58. Yang Y, Yang H, Kusuma J, Shiao S. Validating Accuracy of an Internet-Based Application against USDA Computerized Nutrition Data System for Research on Essential Nutrients among Social-Ethnic Diets for the E-Health Era. Nutrients 2022;14(15):3168 View
  59. Chen Y, Ji M, Wu Y, Wang Q, Deng Y, Liu Y, Wu F, Liu M, Guo Y, Fu Z, Zheng X. An Intelligent Individualized Cardiovascular App for Risk Elimination (iCARE) for Individuals With Coronary Heart Disease: Development and Usability Testing Analysis. JMIR mHealth and uHealth 2021;9(12):e26439 View
  60. Baer N, Vietzke J, Schenk L, Jutai J. Middle-aged and older adults’ acceptance of mobile nutrition and fitness apps: A systematic mixed studies review. PLOS ONE 2022;17(12):e0278879 View
  61. Kay M, Miller H, Askew S, Spaulding E, Chisholm M, Christy J, Yang Q, Steinberg D. Patterns of Engagement With an Application-Based Dietary Self-Monitoring Tool Within a Randomized Controlled Feasibility Trial. AJPM Focus 2022;1(2):100037 View
  62. Grau L, Larkin K, Lalloo C, Stinson J, Zempsky W, Ball S, Buono F. Perspectives on adapting a mobile application for pain self-management in neurofibromatosis type 1: results of online focus group discussions with individuals living with neurofibromatosis type 1 and pain management experts. BMJ Open 2022;12(7):e056692 View
  63. Modrzejewska J, Modrzejewska A, Czepczor-Bernat K, Matusik P, Mahmoud A. The role of body mass index, healthy eating-related apps and educational activities on eating motives and behaviours among women during the COVID-19 pandemic: A cross sectional study. PLOS ONE 2022;17(3):e0266016 View
  64. Ji W, Shi W, Li X, Shan X, Zhou J, Liu F, Qi F. Evaluation of the Effectiveness of Remote Monitoring to Establish a Community Health Intervention During COVID-19: A Community Intervention Trial. Telemedicine and e-Health 2023;29(2):253 View
  65. Scarry A, Rice J, O’Connor E, Tierney A. Usage of Mobile Applications or Mobile Health Technology to Improve Diet Quality in Adults. Nutrients 2022;14(12):2437 View
  66. Manners R, Adewopo J, Niyibituronsa M, Remans R, Ghosh A, Schut M, Egoeh S, Kilwenge R, Fraenzel A. Leveraging Digital Tools and Crowdsourcing Approaches to Generate High-Frequency Data for Diet Quality Monitoring at Population Scale in Rwanda. Frontiers in Sustainable Food Systems 2022;5 View
  67. Jonvik K, King M, Rollo I, Stellingwerff T, Pitsiladis Y. New Opportunities to Advance the Field of Sports Nutrition. Frontiers in Sports and Active Living 2022;4 View
  68. Milne-Ives M, Homer S, Andrade J, Meinert E. Associations Between Behavior Change Techniques and Engagement With Mobile Health Apps: Protocol for a Systematic Review. JMIR Research Protocols 2022;11(3):e35172 View
  69. Granheim S, Løvhaug A, Terragni L, Torheim L, Thurston M. Mapping the digital food environment: A systematic scoping review. Obesity Reviews 2022;23(1) View
  70. Arora N, Pulimamidi S, Yadav H, Jain S, Glover J, Dombrowski K, Hernandez B, Sarma A, Aneja R. Intermittent fasting with ketogenic diet: A combination approach for management of chronic diseases. Clinical Nutrition ESPEN 2023;54:166 View
  71. Rycroft C, Beer S, Corrigan N, Cade J. Using Social Media to Collect Dietary Information for Public Health Policy. Nutrients 2022;14(24):5322 View
  72. Höchsmann C, Fearnbach N, Dorling J, Fazzino T, Myers C, Apolzan J, Martin C. Preference, Expected Burden, and Willingness to Use Digital and Traditional Methods to Assess Food and Alcohol Intake. Nutrients 2021;13(10):3340 View
  73. Rochat J, Ehrler F, Siebert J, Ricci A, Garretas Ruiz V, Lovis C. Usability Testing of a Patient-Centered Mobile Health App for Supporting and Guiding the Pediatric Emergency Department Patient Journey: Mixed Methods Study. JMIR Pediatrics and Parenting 2022;5(1):e25540 View
  74. Bzikowska-Jura A, Sobieraj P, Raciborski F. Low Comparability of Nutrition-Related Mobile Apps against the Polish Reference Method—A Validity Study. Nutrients 2021;13(8):2868 View
  75. Kaiser B, Stelzl T, Finglas P, Gedrich K. The Assessment of a Personalized Nutrition Tool (eNutri) in Germany: Pilot Study on Usability Metrics and Users’ Experiences. JMIR Formative Research 2022;6(8):e34497 View
  76. Lee H, Ahn J, Lee J. Development and Validation of a Questionnaire on the Feasibility of a Mobile Dietary Self-Monitoring Application. Korean Journal of Community Nutrition 2022;27(2):146 View
  77. Lin A, Morgan N, Ward D, Tangney C, Alshurafa N, Van Horn L, Spring B. Comparative Validity of Mostly Unprocessed and Minimally Processed Food Items Differs Among Popular Commercial Nutrition Apps Compared with a Research Food Database. Journal of the Academy of Nutrition and Dietetics 2022;122(4):825 View
  78. Slazus C, Ebrahim Z, Koen N. Mobile health apps: An assessment of needs, perceptions, usability, and efficacy in changing dietary choices. Nutrition 2022;101:111690 View
  79. Martyn-Nemeth P, Hayman L. Digital Technology in Cardiovascular Health. Journal of Cardiovascular Nursing 2023;38(3):207 View
  80. Kahkoska A, Cristello Sarteau A, Crowley M. Delivering on the Promise of Technology to Augment Behavioral Interventions in Type 2 Diabetes. Diabetes Care 2023;46(5):918 View
  81. Liu Y, Jiang H, Qi Y, Yang J, Civitarese G. m-Health of Nutrition: Improving Nutrition Services with Smartphone and Machine Learning. Mobile Information Systems 2023;2023:1 View
  82. Martin-Vicario L, Bustos Díaz J, Nicolas-Sans R, Yan Z. Weight Loss App Descriptors in App Stores: A Qualitative Analysis of the Spanish Market. Human Behavior and Emerging Technologies 2023;2023:1 View
  83. Ross E, Al Ozairi E, Al qabandi N, Jamison R. Optimizing an mHealth Program to Promote Type 2 Diabetes Prevention in High-Risk Individuals: Cross-Sectional Questionnaire Study. JMIR Formative Research 2023;7:e45977 View
  84. Khademzadeh S, Ghazisaeidi M, Toosi M, Roshanpoor A, Mehraeen E. An intelligent recommender system for people who are prone to fatty liver disease. Informatics in Medicine Unlocked 2023;41:101315 View
  85. Gioia S, Vlasac I, Babazadeh D, Fryou N, Do E, Love J, Robbins R, Dashti H, Lane J. Mobile Apps for Dietary and Food Timing Assessment: Evaluation for Use in Clinical Research. JMIR Formative Research 2023;7:e35858 View
  86. Alnooh G, Alessa T, Noorwali E, Albar S, Williams E, de Witte L, Hawley M. Identification of the Most Suitable Mobile Apps to Support Dietary Approaches to Stop Hypertension (DASH) Diet Self-Management: Systematic Search of App Stores and Content Analysis. Nutrients 2023;15(15):3476 View
  87. Cohen Y, Valdés-Mas R, Elinav E. The Role of Artificial Intelligence in Deciphering Diet–Disease Relationships: Case Studies. Annual Review of Nutrition 2023;43(1):225 View
  88. Abdul Khalil N, Mohd Mydin F, Moy F, Diviani N. Healthy adults’ views and experiences on behavior change strategies in mobile applications for diet monitoring: A single centre qualitative study. PLOS ONE 2023;18(11):e0292390 View
  89. Benthem de Grave R, Bull C, Monjardino de Souza Monteiro D, Margariti E, McMurchy G, Hutchinson J, Smeddinck J. Smartphone Apps for Food Purchase Choices: Scoping Review of Designs, Opportunities, and Challenges. Journal of Medical Internet Research 2024;26:e45904 View
  90. Martin-Vicario L, Martínez-Sánchez M, Nicolas-Sans R. Factors influencing perceived usefulness of a branded weight-loss app. British Food Journal 2024;126(4):1725 View
  91. Goh C, Zheng K, Chua W, Nguyen T, Liu C, Koh C, Lee G, Tay C, Ooi B, Wong M. Development of a dental diet-tracking mobile app for improved caries-related dietary behaviours: Key features and pilot evaluation of quality. DIGITAL HEALTH 2024;10 View
  92. Banal M, Bongga D, Angbengco J, Amarra S, Panlasigui L. MyFitnessPal smartphone application: relative validity and intercoder reliability among dietitians in assessing energy and macronutrient intakes of selected Filipino adults with obesity. BMJ Nutrition, Prevention & Health 2024:e000770 View
  93. Guedry S, Langley B, Schaefer K, Hanes D. Integrative medicine for hypermobility spectrum disorders (HSD) and Ehlers-Danlos syndromes (EDS): a feasibility study. Disability and Rehabilitation 2024:1 View
  94. İzgi Tezcan C, Suna G, Karabulak A. Yetişkin Bireylerde E-Sağlık Mobil Uygulama Destekli Beslenme ve Egzersiz Programlarının Vücut Kompozisyonu ve Bazı Kan Parametreleri Üzerine Etkisinin İncelenmesi. Süleyman Demirel Üniversitesi Sağlık Bilimleri Dergisi 2024;15(1):17 View
  95. An R, Perez-Cruet J, Wang X, Yang Y. Build Deep Neural Network Models to Detect Common Edible Nuts from Photos and Estimate Nutrient Portfolio. Nutrients 2024;16(9):1294 View
  96. Annuzzi G, Apicella A, Arpaia P, Bozzetto L, Criscuolo S, De Benedetto E, Pesola M, Prevete R. Exploring Nutritional Influence on Blood Glucose Forecasting for Type 1 Diabetes Using Explainable AI. IEEE Journal of Biomedical and Health Informatics 2024;28(5):3123 View

Books/Policy Documents

  1. Cho P, Singh K, Dunn J. Artificial Intelligence in Medicine. View
  2. Ofori M, El-Gayar O. Optimizing Health Monitoring Systems With Wireless Technology. View
  3. Marvel F, Huynh P, Martin S. Precision Medicine in Cardiovascular Disease Prevention. View
  4. Karnavat T, Bhatia J, Ghosh S, Sen S. Mobile and Ubiquitous Systems: Computing, Networking and Services. View
  5. Mohammed S, Ighe M, Nordin A. Advances on Intelligent Informatics and Computing. View
  6. Weech M, Fallaize R, Kelly E, Hwang F, Franco R, Lovegrove J. Smartphone Apps for Health and Wellness. View
  7. Cerra Z, Apicella M. Smartphone Apps for Health and Wellness. View
  8. Gupta H, Jha S, Handa S, Gairola T. International Conference on Innovative Computing and Communications. View
  9. Li X, Jiang A. Design, User Experience, and Usability. View
  10. Lurz M, Prommegger B, Böhm M, Krcmar H. Human-Computer Interaction. View