Butte, Atul J.

Evidence for benefit of statins to modify cognitive decline and risk in Alzheimer’s disease

Geifman, N., Brinton, R. D., Kennedy, R. E., Schneider, L. S., & Butte, A. J. (2017) · Alzheimer's Research & Therapy

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 191

Hematopoietic Stem Cell Quiescence Is Maintained by Compound Contributions of the Retinoblastoma Gene Family

Viatour, P., Somervaille, T. C., Venkatasubrahmanyam, S., Kogan, S., McLaughlin, M. E., Weissman, I. L., Butte, A. J., Passegué, E., & Sage, J. (2008) · Cell Stem Cell

Hematopoietic Stem Cell TransplantationMesenchymal stem cell research

Cited by 178

Expression-based genome-wide association study links the receptor CD44 in adipose tissue with type 2 diabetes

Kodama, K., Horikoshi, M., Toda, K., Yamada, S., Hara, K., Irie, J., Sirota, M., Morgan, A. A., Chen, R., Ohtsu, H., et al. (2012) · Proceedings of the National Academy of Sciences

Adipokines, Inflammation, and Metabolic DiseasesGenetic Associations and Epidemiology

Cited by 171

Prototype of running clinical trials in an untrustworthy environment using blockchain

Wong, D. R., Bhattacharya, S., & Butte, A. J. (2019) · Nature Communications

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 160

Defective signaling in the JAK-STAT pathway tracks with chronic inflammation and cardiovascular risk in aging humans

Shen-Orr, S. S., Furman, D., Kidd, B. A., Hadad, F., Lovelace, P., Huang, Y.-W., Rosenberg-Hasson, Y., Mackey, S., Grisar, F. A. G., Pickman, Y., et al. (2016) · Cell Systems

Cytokine Signaling Pathways and InteractionsAdipokines, Inflammation, and Metabolic Diseases

Cited by 154

Use of a Large Language Model to Assess Clinical Acuity of Adults in the Emergency Department

Williams, C. Y. K., Zack, T., Miao, B. Y., Sushil, M., Wang, M., Kornblith, A. E., & Butte, A. J. (2024) · JAMA Network Open

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 148

Evaluating large language models as agents in the clinic

Mehandru, N., Miao, B. Y., Almaraz, E. R., Sushil, M., Butte, A. J., & Alaa, A. (2024) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 143

Characteristics and challenges of the clinical pipeline of digital therapeutics

Patel, N. A., & Butte, A. J. (2020) · npj Digital Medicine

Digital Mental Health InterventionsMobile Health and mHealth Applications

Cited by 143

Evaluating the use of large language models to provide clinical recommendations in the Emergency Department

Williams, C. Y. K., Miao, B. Y., Kornblith, A. E., & Butte, A. J. (2024) · Nature Communications

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 119

The case for algorithmic stewardship for artificial intelligence and machine learning technologies

Eaneff, S., Obermeyer, Z., & Butte, A. J. (2020) · JAMA

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 101

Population genetic inference from personal genome data: impact of ancestry and admixture on human genomic variation

Kidd, J. M., Gravel, S., Byrnes, J., Moreno-Estrada, A., Musharoff, S., Bryc, K., Degenhardt, J. D., Brisbin, A., Sheth, V., Chen, R., et al. (2012) · The American Journal of Human Genetics

Forensic and Genetic ResearchGenetic diversity and population structure

Cited by 95

Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings

Nelson, C. A., Butte, A. J., & Baranzini, S. E. (2019) · Nature Communications

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 85

Anti-CD44 Antibody Treatment Lowers Hyperglycemia and Improves Insulin Resistance, Adipose Inflammation, and Hepatic Steatosis in Diet-Induced Obese Mice

Kodama, K., Toda, K., Morinaga, S., Yamada, S., & Butte, A. J. (2015) · Diabetes

Adipokines, Inflammation, and Metabolic DiseasesAdipose Tissue and Metabolism

Cited by 85

AI in Medicine—JAMA’s Focus on Clinical Outcomes, Patient-Centered Care, Quality, and Equity

Khera, R., Butte, A. J., Berkwits, M., Hswen, Y., Flanagin, A., Park, H., Curfman, G., & Bibbins-Domingo, K. (2023) · JAMA

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 78

Comparing Ethnicity-Specific Reference Intervals for Clinical Laboratory Tests from EHR Data

Rappoport, N., Paik, H., Oskotsky, B., Tor, R., Ziv, E., Zaitlen, N., & Butte, A. J. (2018) · The Journal of Applied Laboratory Medicine

Clinical Laboratory Practices and Quality ControlRace, Genetics, and Society

Cited by 49

Electrocardiogram Detection of Pulmonary Hypertension Using Deep Learning

ARAS, M. A., ABREAU, S., MILLS, H., RADHAKRISHNAN, L., KLEIN, L., MANTRI, N., RUBIN, B., BARRIOS, J., CHEHOUD, C., KOGAN, E., et al. (2023) · Journal of Cardiac Failure

ECG Monitoring and AnalysisPulmonary Hypertension Research and Treatments

Cited by 46

PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model

Glicksberg, B. S., Oskotsky, B., Thangaraj, P. M., Giangreco, N., Badgeley, M. A., Johnson, K. W., Datta, D., Rudrapatna, V. A., Rappoport, N., Shervey, M. M., et al. (2019) · Bioinformatics

Electronic Health Records SystemsMachine Learning in Healthcare

Cited by 45

Evaluating large language models for drafting emergency department encounter summaries

Williams, C. Y. K., Bains, J., Tang, T., Patel, K., Lucas, A. N., Chen, F., Miao, B. Y., Butte, A. J., & Kornblith, A. E. (2025) · PLOS Digital Health

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 41

Evaluating Large Language Models for Drafting Emergency Department Discharge Summaries

Williams, C. Y. K., Bains, J., Tang, T., Patel, K., Lucas, A. N., Chen, F., Miao, B. Y., Butte, A. J., & Kornblith, A. E. (2024) · medRxiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 35

Predicting inpatient medication orders from electronic health record data

Rough, K., Dai, A. M., Zhang, K., Xue, Y., Vardoulakis, L. M., Cui, C., Butte, A. J., Howell, M. D., & Rajkomar, A. (2020) · Clinical Pharmacology & Therapeutics

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 28