Nadkarni, Girish N.

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Taliun, D., Harris, D. N., Kessler, M. D., Carlson, J., Szpiech, Z. A., Torres, R., Taliun, S. A. G., Corvelo, A., Gogarten, S. M., Kang, H. M., et al. (2021) · Nature

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 2,213

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

Mahajan, A., Taliun, D., Thurner, M., Robertson, N. R., Torres, J. M., Rayner, N. W., Payne, A. J., Steinthorsdottir, V., Scott, R. A., Grarup, N., et al. (2018) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 1,744

Genetic analyses of diverse populations improves discovery for complex traits

Wojcik, G. L., Graff, M., Nishimura, K. K., Tao, R., Haessler, J., Gignoux, C. R., Highland, H. M., Patel, Y. M., Sorokin, E. P., Avery, C. L., et al. (2019) · Nature

Genetic Associations and EpidemiologyRace, Genetics, and Society

Cited by 1,033

The power of genetic diversity in genome-wide association studies of lipids

Graham, S. E., Clarke, S. L., Wu, K.-H. H., Kanoni, S., Zajac, G. J. M., Ramdas, S., Surakka, I., Ntalla, I., Vedantam, S., Winkler, T. W., et al. (2021) · Nature

Genetic Associations and EpidemiologyLipoproteins and Cardiovascular Health

Cited by 972

Factors associated with death in critically ill patients with coronavirus disease 2019 in the US

Gupta, S., Hayek, S. S., Wang, W., Chan, L., Mathews, K. S., Melamed, M. L., Brenner, S. K., Leonberg-Yoo, A., Schenck, E. J., Radbel, J., et al. (2020) · JAMA Internal Medicine

COVID-19 Clinical Research StudiesSepsis Diagnosis and Treatment

Cited by 957

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

Multinational Assessment of Accuracy of Equations for Predicting Risk of Kidney Failure: A Meta-analysis

Tangri, N., Grams, M. E., Levey, A. S., Coresh, J., Appel, L. J., Astor, B. C., Chodick, G., Collins, A. J., Djurdjev, O., Elley, C. R., et al. (2016) · JAMA

Chronic Kidney Disease and DiabetesDialysis and Renal Disease Management

Cited by 737

Inherited causes of clonal haematopoiesis in 97,691 whole genomes

Bick, A. G., Weinstock, J. S., Nandakumar, S. K., Fulco, C. P., Bao, E. L., Zekavat, S. M., Szeto, M. D., Liao, X., Leventhal, M. J., Nasser, J., et al. (2020) · Nature

Acute Myeloid Leukemia ResearchGenetic Associations and Epidemiology

Cited by 733

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Mahajan, A., Spracklen, C. N., Zhang, W., Ng, M. C. Y., Petty, L. E., Kitajima, H., Yu, G. Z., Rüeger, S., Speidel, L., Kim, Y. J., et al. (2022) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 704

The Polygenic and Monogenic Basis of Blood Traits and Diseases

Vuckovic, D., Bao, E. L., Akbari, P., Lareau, C. A., Mousas, A., Jiang, T., Chen, M.-H., Raffield, L. M., Tardaguila, M., Huffman, J. E., et al. (2020) · Cell

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 671

Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations

Chen, M.-H., Raffield, L. M., Mousas, A., Sakaue, S., Huffman, J. E., Moscati, A., Trivedi, B., Jiang, T., Akbari, P., Vuckovic, D., et al. (2020) · Cell

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 661

Association Between Early Treatment With Tocilizumab and Mortality Among Critically Ill Patients With COVID-19

Gupta, S., Wang, W., Hayek, S. S., Chan, L., Mathews, K. S., Melamed, M. L., Brenner, S. K., Leonberg-Yoo, A., Schenck, E. J., Radbel, J., et al. (2021) · JAMA Internal Medicine

COVID-19 Clinical Research StudiesRespiratory Support and Mechanisms

Cited by 535

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

Mahajan, A., Wessel, J., Willems, S. M., Zhao, W., Robertson, N. R., Chu, A. Y., Gan, W., Kitajima, H., Taliun, D., Rayner, N. W., et al. (2018) · Nature Genetics

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 442

Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes: An Individual-Participant Data Meta-Analysis

Writing Group for the CKD Prognosis Consortium, Appel, L. J., Grams, M., Woodward, M., Harris, K., Arima, H., Chalmers, J., Yatsuya, H., Tamakoshi, K., Li, Y., et al. (2023) · JAMA

Chronic Kidney Disease and DiabetesAcute Kidney Injury Research

Cited by 396

Change in albuminuria and subsequent risk of end-stage kidney disease: an individual participant-level consortium meta-analysis of observational studies

Coresh, J., Heerspink, H. J. L., Sang, Y., Matsushita, K., Arnlov, J., Astor, B. C., Black, C., Brunskill, N. J., Carrero, J.-J., Feldman, H. I., et al. (2019) · The Lancet Diabetes & Endocrinology

Chronic Kidney Disease and DiabetesAcute Kidney Injury Research

Cited by 338

Pathology of Peripheral Artery Disease in Patients With Critical Limb Ischemia

Narula, N., Dannenberg, A. J., Olin, J. W., Bhatt, D. L., Johnson, K. W., Nadkarni, G., Min, J., Torii, S., Poojary, P., Anand, S. S., et al. (2018) · Journal of the American College of Cardiology

Peripheral Artery Disease ManagementAortic Thrombus and Embolism

Cited by 326

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

Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis

Dapas, M., Lin, F. T. J., Nadkarni, G. N., Sisk, R., Legro, R. S., Urbanek, M., Hayes, M. G., & Dunaif, A. (2020) · PLOS Medicine

Ovarian function and disordersGenetic and Kidney Cyst Diseases

Cited by 297

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

Large Language Models and Empathy: Systematic Review

Sorin, V., Brin, D., Barash, Y., Konen, E., Charney, A., Nadkarni, G., & Klang, E. (2024) · Journal of Medical Internet Research

Artificial Intelligence in Healthcare and EducationEmpathy and Medical Education

Cited by 240

Multi-model assurance analysis showing large language models are highly vulnerable to adversarial hallucination attacks during clinical decision support

Omar, M., Sorin, V., Collins, J. D., Reich, D., Freeman, R., Gavin, N., Charney, A., Stump, L., Bragazzi, N. L., Nadkarni, G. N., et al. (2025) · Communications Medicine

Adversarial Robustness in Machine LearningArtificial Intelligence in Healthcare and Education

Cited by 204

Acute kidney injury in patients on SGLT2 inhibitors: a propensity-matched analysis

Nadkarni, G. N., Ferrandino, R., Chang, A., Surapaneni, A., Chauhan, K., Poojary, P., Saha, A., Ferket, B., Grams, M. E., & Coca, S. G. (2017) · Diabetes Care

Acute Kidney Injury ResearchDiabetes Treatment and Management

Cited by 188