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

Books/Policy Documents

  1. Iqbal H, Chawla U. The Fusion of Internet of Things, Artificial Intelligence, and Cloud Computing in Health Care. View