Last Posted: Aug 02, 2019
- [Screening and management of retinal diseases using digital medicine].
Gerendas B S et al. Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft 2018 Sep 115(9) 728-736 - Application of Machine Learning to Predict Dietary Lapses During Weight Loss.
Goldstein Stephanie P et al. Journal of diabetes science and technology 2018 12(5) 1045-1052 - Pharmacogenetics of Antidiabetic Drugs.
Srinivasan Shylaja et al. Advances in pharmacology (San Diego, Calif.) 2018 83361-389 - Clinical burden of illness in patients with phenylketonuria (PKU) and associated comorbidities - a retrospective study of German health insurance claims data.
Trefz K F et al. Orphanet journal of rare diseases 2019 Jul 14(1) 181 - Study in Africa Yields New Diabetes Gene
NIH Directors' Blog, July 30, 2019 - Heterogeneity of diabetes: heralding the era of precision medicine.
Del Prato Stefano et al. The lancet. Diabetes & endocrinology 2019 Jul - Predicting nonroutine discharge after elective spine surgery: external validation of machine learning algorithms.
Stopa Brittany M et al. Journal of neurosurgery. Spine 2019 Jul 1-6 - The Value of Automated Diabetic Retinopathy Screening With the EyeArt System: A Study of More Than 100,000 Consecutive Encounters from People with Diabetes.
Bhaskaranand Malavika et al. Diabetes technology & therapeutics 2019 Jul - TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records.
Bernardini Michele et al. Computers in biology and medicine 2019 Jul 112103358 - Attitudes Regarding Enrollment in a Genetic Research Project: An Informed Consent Simulation Study Comparing Views of People With Depression, Diabetes, and Neither Condition.
Kim Jane Paik et al. Journal of empirical research on human research ethics : JERHRE 2019 Jul 1556264619862467
No hay comentarios:
Publicar un comentario