Published on in Vol 22, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16922, first published .
Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists

Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists

Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists

Journals

  1. Kim K. Real World Data and Artificial Intelligence in Diabetology. The Journal of Korean Diabetes 2020;21(3):140 View
  2. Elhadi M, Msherghi A, Elhadi A, Ashini A, Alsoufi A, Bin Alshiteewi F, Elmabrouk A, Alsuyihili A, Elgherwi A, Elkhafeefi F, Abdulrazik S, Tarek A. Utilization of Telehealth Services in Libya in Response to the COVID-19 Pandemic: Cross-sectional Analysis. JMIR Medical Informatics 2021;9(2):e23335 View
  3. Hassan S, Dhali M, Zaman F, Tanveer M. BIG DATA AND PREDICTIVE ANALYTICS IN HEALTHCARE IN BANGLADESH: REGULATORY CHALLENGES. Heliyon 2021:e07179 View
  4. Begg A. Diabetes care: is big data the future?. Practical Diabetes 2022;39(3):7 View
  5. Kulzer B. Künstliche Intelligenz (KI) in der Diabetologie – jetzt und in der Zukunft. Die Diabetologie 2023;19(1):35 View
  6. Benítez-Andrades J, Alija-Pérez J, Vidal M, Pastor-Vargas R, García-Ordás M. Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)–Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study. JMIR Medical Informatics 2022;10(2):e34492 View
  7. Hasanzad M, Aghaei Meybodi H, Sarhangi N, Larijani B. Artificial intelligence perspective in the future of endocrine diseases. Journal of Diabetes & Metabolic Disorders 2022;21(1):971 View
  8. Karatas M, Eriskin L, Deveci M, Pamucar D, Garg H. Big Data for Healthcare Industry 4.0: Applications, challenges and future perspectives. Expert Systems with Applications 2022;200:116912 View
  9. Yu Z, Luo W, Tse R, Pau G. DMNet: A Personalized Risk Assessment Framework for Elderly People With Type 2 Diabetes. IEEE Journal of Biomedical and Health Informatics 2023;27(3):1558 View
  10. Masi D, Zilich R, Candido R, Giancaterini A, Guaita G, Muselli M, Ponzani P, Santin P, Verda D, Musacchio N. Uncovering Predictors of Lipid Goal Attainment in Type 2 Diabetes Outpatients Using Logic Learning Machine: Insights from the AMD Annals and AMD Artificial Intelligence Study Group. Journal of Clinical Medicine 2023;12(12):4095 View
  11. Cestonaro C, Delicati A, Marcante B, Caenazzo L, Tozzo P. Defining medical liability when artificial intelligence is applied on diagnostic algorithms: a systematic review. Frontiers in Medicine 2023;10 View
  12. Spoladore D, Colombo V, Campanella V, Lunetta C, Mondellini M, Mahroo A, Cerri F, Sacco M. A Knowledge-based Decision Support System for recommending safe recipes to individuals with dysphagia. Computers in Biology and Medicine 2024;171:108193 View
  13. Spoladore D, Tosi M, Lorenzini E. Ontology-based decision support systems for diabetes nutrition therapy: A systematic literature review. Artificial Intelligence in Medicine 2024;151:102859 View
  14. Sharma K, Shadni S, Batra J, Gupta S. An analysis of parameter effecting diabetes among people using machine learning and AI. SSRN Electronic Journal 2024 View

Books/Policy Documents

  1. Hong N, Park Y, You S, Rhee Y. Artificial Intelligence in Medicine. View
  2. Hong N, Park Y, You S, Rhee Y. Artificial Intelligence in Medicine. View
  3. Rajeswari S, Ponnusamy V. Integrating AI in IoT Analytics on the Cloud for Healthcare Applications. View
  4. . Enzyme‐Based Organic Synthesis. View
  5. Akter L, Ferdib-Al-Islam . Proceedings of International Conference on Emerging Technologies and Intelligent Systems. View