Scheinker, David

Machine learning and atherosclerotic cardiovascular disease risk prediction in a multi-ethnic population

Ward, A., Sarraju, A., Chung, S., Li, J., Harrington, R., Heidenreich, P., Palaniappan, L., Scheinker, D., & Rodriguez, F. (2020) · npj Digital Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 112

Uninterrupted continuous glucose monitoring access is associated with a decrease in HbA1c in youth with type 1 diabetes and public insurance

Addala, A., Maahs, D. M., Scheinker, D., Chertow, S., Leverenz, B., & Prahalad, P. (2020) · Pediatric Diabetes

Diabetes Management and ResearchDiabetes Management and Education

Cited by 83

Teamwork, targets, technology, and tight control in newly diagnosed type 1 diabetes: the Pilot 4T Study

Prahalad, P., Ding, V. Y., Zaharieva, D. P., Addala, A., Johari, R., Scheinker, D., Desai, M., Hood, K., & Maahs, D. M. (2022) · The Journal of Clinical Endocrinology & Metabolism

Diabetes Management and ResearchDiabetes Management and Education

Cited by 82

A New Technology-Enabled Care Model for Pediatric Type 1 Diabetes

Scheinker, D., Prahalad, P., Johari, R., Maahs, D. M., & Majzun, R. (2022) · NEJM Catalyst

Diabetes Management and ResearchTelemedicine and Telehealth Implementation

Cited by 25