Zou, James

Deep learning evaluation of biomarkers from echocardiogram videos

Hughes, J. W., Yuan, N., He, B., Ouyang, J., Ebinger, J., Botting, P., Lee, J., Theurer, J., Tooley, J. E., Nieman, K., et al. (2021) · EBioMedicine

Artificial Intelligence in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 71

A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agents

Huang, W.-C., Zhang, W., Liang, Y., Bei, Y., Chen, Y., Feng, T., Pan, X., Tan, Z., Wang, Y., Wei, T., et al. (2026) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence Applications

Cited by 70

MedAgentBench: a virtual EHR environment to benchmark medical LLM agents

Jiang, Y., Black, K. C., Geng, G., Park, D., Zou, J., Ng, A. Y., & Chen, J. H. (2025) · NEJM AI

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 66

Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study

Ouyang, D., Theurer, J., Stein, N. R., Hughes, J. W., Elias, P., He, B., Yuan, N., Duffy, G., Sandhu, R. K., Ebinger, J., et al. (2024) · The Lancet Digital Health

ECG Monitoring and AnalysisCardiac, Anesthesia and Surgical Outcomes

Cited by 64

Do Humans Trust Advice More if it Comes from AI?: An Analysis of Human-AI Interactions

Vodrahalli, K., Daneshjou, R., Gerstenberg, T., & Zou, J. (2022) · Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

Human-Automation Interaction and SafetySocial Robot Interaction and HRI

Cited by 63

The Virtual Lab: AI Agents Design New SARS-CoV-2 Nanobodies with Experimental Validation

Swanson, K., Wu, W., Bulaong, N. L., Pak, J. E., & Zou, J. (2024) · bioRxiv (Cold Spring Harbor Laboratory)

SARS-CoV-2 and COVID-19 Researchvaccines and immunoinformatics approaches

Cited by 56

Mapping the Increasing Use of LLMs in Scientific Papers

Liang, W., Zhang, Y., Wu, Z., Lepp, H., Ji, W., Zhao, X., Cao, H., Liu, S., He, S., Huang, Z., et al. (2024) · arXiv

scientometrics and bibliometrics researchAcademic Writing and Publishing

Cited by 55

How well do LLMs cite relevant medical references? An evaluation framework and analyses

Wu, K., Wu, E., Cassasola, A., Zhang, A., Wei, K., Nguyen, T., Riantawan, S., Riantawan, P. S., Ho, D. E., & Zou, J. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 41

GPT detectors are biased against non-native English writers

Liang, W., Yuksekgonul, M., Mao, Y., Wu, E., & Zou, J. (2023) · arXiv

Authorship Attribution and ProfilingEthics and Social Impacts of AI

Cited by 40

Squidiff: predicting cellular development and responses to perturbations using a diffusion model

He, S., Zhu, Y., Tavakol, D. N., Ye, H., Lao, Y.-H., Zhu, Z., Xu, C., Chauhan, S., Garty, G., Tomer, R., et al. (2026) · Nature Methods

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 38

Brain proteomic analysis implicates actin filament processes and injury response in resilience to Alzheimer’s disease

Huang, Z., Merrihew, G. E., Larson, E. B., Park, J., Plubell, D., Fox, E. J., Montine, K. S., Latimer, C. S., Dirk Keene, C., Zou, J. Y., et al. (2023) · Nature Communications

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 37

The widespread adoption of large language model-assisted writing across society

Liang, W., Zhang, Y., Codreanu, M., Wang, J., Cao, H., & Zou, J. (2025) · Patterns

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 35

CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models

Xia, P., Chen, Z., Tian, J., Gong, Y., Hou, R., Xu, Y., Wu, Z., Fan, Z., Zhou, Y., Zhu, K., et al. (2024) · Advances in Neural Information Processing Systems 37

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 32

Scaling Adoption of Medical AI — Reimbursement from Value-Based Care and Fee-for-Service Perspectives

Abramoff, M. D., Dai, T., & Zou, J. (2024) · NEJM AI

Healthcare Policy and ManagementArtificial Intelligence in Healthcare and Education

Cited by 32

Serum Potassium Monitoring Using AI-Enabled Smartwatch Electrocardiograms

Chiu, I.-M., Wu, P.-J., Zhang, H., Hughes, J. W., Rogers, A. J., Jalilian, L., Perez, M., Lin, C.-H. R., Lee, C.-T., Zou, J., et al. (2024) · JACC: Clinical Electrophysiology

ECG Monitoring and AnalysisPotassium and Related Disorders

Cited by 31

National Cancer Institute Workshop on Artificial Intelligence in Radiation Oncology: Training the Next Generation

Kang, J., Thompson, R. F., Aneja, S., Lehman, C., Trister, A., Zou, J., Obcemea, C., & El Naqa, I. (2021) · Practical Radiation Oncology

Artificial Intelligence in Healthcare and EducationAdvances in Oncology and Radiotherapy

Cited by 30

Implications of predicting race variables from medical images

Zou, J., Gichoya, J. W., Ho, D. E., & Obermeyer, Z. (2023) · Science

Race, Genetics, and SocietyArtificial Intelligence in Healthcare and Education

Cited by 30

Development and clinical evaluation of an artificial intelligence support tool for improving telemedicine photo quality

Vodrahalli, K., Ko, J., Chiou, A. S., Novoa, R., Abid, A., Phung, M., Yekrang, K., Petrone, P., Zou, J., & Daneshjou, R. (2023) · JAMA Dermatology

Telemedicine and Telehealth ImplementationArtificial Intelligence in Healthcare and Education

Cited by 30

Explainable differential diagnosis with dual-inference large language models

Zhou, S., Lin, M., Ding, S., Wang, J., Chen, C., Melton, G. B., Zou, J., & Zhang, R. (2025) · npj Health Systems

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 20

Do Humans Trust Advice More if it Comes from AI? An Analysis of Human-AI Interactions

Vodrahalli, K., Daneshjou, R., Gerstenberg, T., & Zou, J. (2021) · arXiv

Human-Automation Interaction and SafetySocial Robot Interaction and HRI

Cited by 16

MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts

Liang, W., & Zou, J. (2022) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Data Classification

Cited by 14

TextGrad: Automatic "Differentiation" via Text

Yuksekgonul, M., Bianchi, F., Boen, J., Liu, S., Huang, Z., Guestrin, C., & Zou, J. (2024) · arXiv

Topic ModelingArtificial Intelligence Applications

Cited by 12

A large-scale randomized study of large language model feedback in peer review

Thakkar, N., Yuksekgonul, M., Silberg, J., Garg, A., Peng, N., Sha, F., Yu, R., Vondrick, C., & Zou, J. (2026) · Nature Machine Intelligence

Publishing and Scholarly CommunicationAcademic Writing and Publishing

Cited by 11

SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals

Thapa, R., He, B., Kjaer, M. R., Moore, H., Ganjoo, G., Mignot, E., & Zou, J. (2024) · arXiv

EEG and Brain-Computer InterfacesSleep and related disorders

Cited by 10