Published on in Vol 8, No 2 (2019): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12539, first published .
Artificial Intelligence for the Detection of Diabetic Retinopathy in Primary Care: Protocol for Algorithm Development

Artificial Intelligence for the Detection of Diabetic Retinopathy in Primary Care: Protocol for Algorithm Development

Artificial Intelligence for the Detection of Diabetic Retinopathy in Primary Care: Protocol for Algorithm Development

Journals

  1. Ellahham S, Ellahham N, Simsekler M. Application of Artificial Intelligence in the Health Care Safety Context: Opportunities and Challenges. American Journal of Medical Quality 2020;35(4):341 View
  2. López Seguí F, Ander Egg Aguilar R, de Maeztu G, García-Altés A, García Cuyàs F, Walsh S, Sagarra Castro M, Vidal-Alaball J. Teleconsultations between Patients and Healthcare Professionals in Primary Care in Catalonia: The Evaluation of Text Classification Algorithms Using Supervised Machine Learning. International Journal of Environmental Research and Public Health 2020;17(3):1093 View
  3. Graham S, Depp C, Lee E, Nebeker C, Tu X, Kim H, Jeste D. Artificial Intelligence for Mental Health and Mental Illnesses: an Overview. Current Psychiatry Reports 2019;21(11) View
  4. Pan X, Jin K, Cao J, Liu Z, Wu J, You K, Lu Y, Xu Y, Su Z, Jiang J, Yao K, Ye J. Multi-label classification of retinal lesions in diabetic retinopathy for automatic analysis of fundus fluorescein angiography based on deep learning. Graefe's Archive for Clinical and Experimental Ophthalmology 2020;258(4):779 View
  5. Hatua A, Subudhi B, T. V, Ghosh A. Early detection of diabetic retinopathy from big data in hadoop framework. Displays 2021;70:102061 View
  6. Ray A, Bhardwaj A, Malik Y, Singh S, Gupta R. Artificial intelligence and Psychiatry: An overview. Asian Journal of Psychiatry 2022;70:103021 View
  7. Lim W, Ho H, Ho H, Chen Y, Lee C, Chen P, Lai F, Jang J, Ko M. Use of multimodal dataset in AI for detecting glaucoma based on fundus photographs assessed with OCT: focus group study on high prevalence of myopia. BMC Medical Imaging 2022;22(1) View
  8. Escalé-Besa A, Yélamos O, Vidal-Alaball J, Fuster-Casanovas A, Miró Catalina Q, Börve A, Ander-Egg Aguilar R, Fustà-Novell X, Cubiró X, Rafat M, López-Sanchez C, Marin-Gomez F. Exploring the potential of artificial intelligence in improving skin lesion diagnosis in primary care. Scientific Reports 2023;13(1) View
  9. Ganesh A, Ramachandiran R. An enhanced affective computing-based framework using machine learning & medical IoT for the efficient pre-emptive decision-making of mental health problems. Journal of Intelligent & Fuzzy Systems 2023:1 View
  10. Catalina Q, Fuster-Casanovas A, Vidal-Alaball J, Escalé-Besa A, Marin-Gomez F, Femenia J, Solé-Casals J. Knowledge and perception of primary care healthcare professionals on the use of artificial intelligence as a healthcare tool. DIGITAL HEALTH 2023;9 View
  11. Kandasamy R, Shubham F, Sharma S. Enigma to Artificial Intelligence. Pondicherry Journal of Nursing 2023;16(3):60 View
  12. Rajagopal S, Sundar Prakash Balaji M, Sivakumar B, Thenmozhi P. Implementation of Deep Learning Techniques Based Artificial Intelligence for Healthcare Data Records. Journal of Electrical Engineering & Technology 2024;19(5):3471 View
  13. Jabbar M, Iqbal H, Chawla U. Patient Satisfaction: The Role of Artificial Intelligence in Healthcare. Journal of Health Management 2024 View
  14. Stolfi F, Abreu H, Sinella R, Nembrini S, Centonze S, Landra V, Brasso C, Cappellano G, Rocca P, Chiocchetti A. Omics approaches open new horizons in major depressive disorder: from biomarkers to precision medicine. Frontiers in Psychiatry 2024;15 View
  15. Injante R, Julca M. Detection of diabetic retinopathy using artificial intelligence: an exploratory systematic review. LatIA 2024;2:112 View

Books/Policy Documents

  1. Iqbal H, Chawla U. The Fusion of Internet of Things, Artificial Intelligence, and Cloud Computing in Health Care. View
  2. Casado-García Á, García-Domínguez M, Heras J, Inés A, Royo D, Zapata M. Computer Aided Systems Theory – EUROCAST 2022. View