Vaid, Akhil

AKI in Hospitalized Patients with COVID-19

Chan, L., Chaudhary, K., Saha, A., Chauhan, K., Vaid, A., Zhao, S., Paranjpe, I., Somani, S., Richter, F., Miotto, R., et al. (2021) · Journal of the American Society of Nephrology

Acute Kidney Injury ResearchCOVID-19 Clinical Research Studies

Cited by 805

Prevalence and Impact of Myocardial Injury in Patients Hospitalized With COVID-19 Infection

Lala, A., Johnson, K. W., Januzzi, J. L., Russak, A. J., Paranjpe, I., Richter, F., Zhao, S., Somani, S., Van Vleck, T., Vaid, A., et al. (2020) · Journal of the American College of Cardiology

COVID-19 Clinical Research StudiesTakotsubo Cardiomyopathy and Associated Phenomena

Cited by 791

Comparing ChatGPT and GPT-4 performance in USMLE soft skill assessments

Brin, D., Sorin, V., Vaid, A., Soroush, A., Glicksberg, B. S., Charney, A. W., Nadkarni, G., & Klang, E. (2023) · Scientific Reports

Artificial Intelligence in Healthcare and EducationInnovations in Medical Education

Cited by 319

Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19

Vaid, A., Jaladanki, S. K., Xu, J., Teng, S., Kumar, A., Lee, S., Somani, S., Paranjpe, I., Freitas, J. K. D., Wanyan, T., et al. (2020) · JMIR Medical Informatics

Machine Learning in HealthcarePrivacy-Preserving Technologies in Data

Cited by 253

A foundation model for clinician-centered drug repurposing

Huang, K., Chandak, P., Wang, Q., Havaldar, S., Vaid, A., Leskovec, J., Nadkarni, G. N., Glicksberg, B. S., Gehlenborg, N., & Zitnik, M. (2024) · Nature Medicine

Computational Drug Discovery MethodsMachine Learning in Healthcare

Cited by 249

Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room

Glicksberg, B. S., Timsina, P., Patel, D., Sawant, A., Vaid, A., Raut, G., Charney, A. W., Apakama, D., Carr, B. G., Freeman, R., et al. (2024) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 82

Pediatric ECG-Based Deep Learning to Predict Left Ventricular Dysfunction and Remodeling

Mayourian, J., La Cava, W. G., Vaid, A., Nadkarni, G. N., Ghelani, S. J., Mannix, R., Geva, T., Dionne, A., Alexander, M. E., Duong, S. Q., et al. (2024) · Circulation

ECG Monitoring and AnalysisArtificial Intelligence in Healthcare

Cited by 59

Using fine-tuned large language models to parse clinical notes in musculoskeletal pain disorders

Vaid, A., Landi, I., Nadkarni, G., & Nabeel, I. (2023) · The Lancet Digital Health

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 45

Multi-center retrospective cohort study applying deep learning to electrocardiograms to identify left heart valvular dysfunction

Vaid, A., Argulian, E., Lerakis, S., Beaulieu-Jones, B. K., Krittanawong, C., Klang, E., Lampert, J., Reddy, V. Y., Narula, J., Nadkarni, G. N., et al. (2023) · Communications Medicine

ECG Monitoring and AnalysisMachine Learning in Healthcare

Cited by 30