Topol, Eric J.

High-performance medicine: the convergence of human and artificial intelligence

Topol, E. J. (2019) · Nature Medicine

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 10,450

Long COVID: major findings, mechanisms and recommendations

Davis, H. E., McCorkell, L., Vogel, J. M., & Topol, E. J. (2023) · Nature Reviews Microbiology

Long-Term Effects of COVID-19COVID-19 Clinical Research Studies

Cited by 4,153

AI in health and medicine

Rajpurkar, P., Chen, E., Banerjee, O., & Topol, E. J. (2022) · Nature Medicine

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 3,212

Foundation models for generalist medical artificial intelligence

Moor, M., Banerjee, O., Abad, Z. S. H., Krumholz, H. M., Leskovec, J., Topol, E. J., & Rajpurkar, P. (2023) · Nature

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 2,028

A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis

Liu, X., Faes, L., Kale, A. U., Wagner, S. K., Fu, D. J., Bruynseels, A., Mahendiran, T., Moraes, G., Shamdas, M., Kern, C., et al. (2019) · The Lancet Digital Health

Artificial Intelligence in Healthcare and EducationAI in cancer detection

Cited by 1,883

Deep learning-enabled medical computer vision

Esteva, A., Chou, K., Yeung, S., Naik, N., Madani, A., Mottaghi, A., Liu, Y., Topol, E., Dean, J., & Socher, R. (2021) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationAdvanced Neural Network Applications

Cited by 1,406

Multimodal biomedical AI

Acosta, J. N., Falcone, G. J., Rajpurkar, P., & Topol, E. J. (2022) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 1,365

State of Telehealth

Dorsey, E. R., & Topol, E. J. (2016) · New England Journal of Medicine

Telemedicine and Telehealth ImplementationHealthcare Systems and Technology

Cited by 1,211

Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies

Nagendran, M., Chen, Y., Lovejoy, C. A., Gordon, A. C., Komorowski, M., Harvey, H., Topol, E. J., Ioannidis, J. P. A., Collins, G. S., & Maruthappu, M. (2020) · BMJ

Artificial Intelligence in Healthcare and EducationAI in cancer detection

Cited by 1,152

Use of antioxidant vitamins for the prevention of cardiovascular disease: meta-analysis of randomised trials

Vivekananthan, D. P., Penn, M. S., Sapp, S. K., Hsu, A., & Topol, E. J. (2003) · The Lancet

Antioxidant Activity and Oxidative StressNutritional Studies and Diet

Cited by 1,083

Human genetic variation and its contribution to complex traits

Frazer, K. A., Murray, S. S., Schork, N. J., & Topol, E. J. (2009) · Nature Reviews Genetics

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 1,073

The imperative for regulatory oversight of large language models (or generative AI) in healthcare

Meskó, B., & Topol, E. J. (2023) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 1,047

A foundation model for generalizable disease detection from retinal images

Zhou, Y., Chia, M. A., Wagner, S. K., Ayhan, M. S., Williamson, D. J., Struyven, R. R., Liu, T., Xu, M., Lozano, M. G., Woodward-Court, P., et al. (2023) · Nature

Retinal Imaging and AnalysisOphthalmology and Visual Health Research

Cited by 1,014

Applications of digital technology in COVID-19 pandemic planning and response

Whitelaw, S., Mamas, M. A., Topol, E., & Van Spall, H. G. C. (2020) · The Lancet Digital Health

COVID-19 Digital Contact TracingData-Driven Disease Surveillance

Cited by 992

The emerging field of mobile health

Steinhubl, S. R., Muse, E. D., & Topol, E. J. (2015) · Science Translational Medicine

Mobile Health and mHealth ApplicationsTechnology and Human Factors in Education and Health

Cited by 822

The n-of-1 clinical trial: the ultimate strategy for individualizing medicine?

Lillie, E. O., Patay, B., Diamant, J., Issell, B., Topol, E. J., & Schork, N. J. (2011) · Personalized Medicine

Statistical Methods in Clinical TrialsPharmaceutical studies and practices

Cited by 706

Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist.

Norgeot, B., Quer, G., Beaulieu-Jones, B. K., Torkamani, A., Dias, R., Gianfrancesco, M., Arnaout, R., Kohane, I. S., Saria, S., Topol, E., et al. (2020) · Nature Medicine

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

Cited by 665

Common vs. rare allele hypotheses for complex diseases

Schork, N. J., Murray, S. S., Frazer, K. A., & Topol, E. J. (2009) · Current Opinion in Genetics & Development

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 649

Adapting to Artificial Intelligence: Radiologists and Pathologists as Information Specialists

Jha, S., & Topol, E. J. (2016) · JAMA

Artificial Intelligence in Healthcare and EducationArtificial Intelligence Applications

Cited by 622

Evaluation of next generation sequencing platforms for population targeted sequencing studies

Harismendy, O., Ng, P. C., Strausberg, R. L., Wang, X., Stockwell, T. B., Beeson, K. Y., Schork, N. J., Murray, S. S., Topol, E. J., Levy, S., et al. (2009) · Genome Biology

Genomics and Phylogenetic StudiesGenomics and Rare Diseases

Cited by 614

Self-supervised learning in medicine and healthcare

Krishnan, R., Rajpurkar, P., & Topol, E. J. (2022) · Nature Biomedical Engineering

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 605

Convergence of atherosclerosis and Alzheimer's disease: inflammation, cholesterol, and misfolded proteins

Casserly, I., & Topol, E. J. (2004) · The Lancet

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 560

Effect of a Home-Based Wearable Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation: The mSToPS Randomized Clinical Trial

Steinhubl, S. R., Waalen, J., Edwards, A. M., Ariniello, L. M., Mehta, R. R., Ebner, G. S., Carter, C., Baca-Motes, K., Felicione, E., Sarich, T., et al. (2018) · JAMA

Atrial Fibrillation Management and OutcomesECG Monitoring and Analysis

Cited by 539

Long COVID science, research and policy

Al-Aly, Z., Davis, H., McCorkell, L., Soares, L., Wulf-Hanson, S., Iwasaki, A., & Topol, E. J. (2024) · Nature Medicine

Long-Term Effects of COVID-19COVID-19 Clinical Research Studies

Cited by 538