Sun, Jimeng

Scientific discovery in the age of artificial intelligence.

Wang, H., Fu, T., Du, Y., Gao, W., Huang, K., Liu, Z., Chandak, P., Liu, S., Van Katwyk, P., Deac, A., et al. (2023) · Nature

Artificial Intelligence ApplicationsMachine Learning in Materials Science

Cited by 1,823

RETAIN: an interpretable predictive model for healthcare using reverse time attention mechanism

Choi, E., Bahadori, M. T., Kulas, J. A., Schuetz, A., Stewart, W. F., & Sun, J. (2016) · arXiv

Machine Learning in HealthcareExplainable Artificial Intelligence (XAI)

Cited by 1,029

Using recurrent neural network models for early detection of heart failure onset

Choi, E., Schuetz, A., Stewart, W. F., & Sun, J. (2017) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 928

Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review

Xiao, C., Choi, E., & Sun, J. (2018) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 792

GRAM: Graph-based Attention Model for Healthcare Representation Learning

Choi, E., Bahadori, M. T., Song, L., Stewart, W. F., & Sun, J. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 637

Explainable Prediction of Medical Codes from Clinical Text

Mullenbach, J., Wiegreffe, S., Duke, J., Sun, J., & Eisenstein, J. (2018) · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 597

Multi-layer Representation Learning for Medical Concepts

Choi, E., Bahadori, M. T., Searles, E., Coffey, C., Thompson, M., Bost, J., Tejedor-Sojo, J., & Sun, J. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 469

GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination

Shang, J., Xiao, C., Ma, T., Li, H., & Sun, J. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence

Machine Learning in HealthcareRecommender Systems and Techniques

Cited by 345

Pre-training of Graph Augmented Transformers for Medication Recommendation

Shang, J., Ma, T., Xiao, C., & Sun, J. (2019) · Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence

Machine Learning in HealthcareRecommender Systems and Techniques

Cited by 311

RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records

Kwon, B. C., Choi, M.-J., Kim, J. T., Choi, E., Kim, Y. B., Kwon, S., Sun, J., & Choo, J. (2019) · IEEE Transactions on Visualization and Computer Graphics

Data Visualization and AnalyticsExplainable Artificial Intelligence (XAI)

Cited by 294

Expert-level sleep scoring with deep neural networks

Biswal, S., Sun, H., Goparaju, B., Westover, M. B., Sun, J., & Bianchi, M. T. (2018) · Journal of the American Medical Informatics Association

EEG and Brain-Computer InterfacesSleep and related disorders

Cited by 290

Matching patients to clinical trials with large language models

Jin, Q., Wang, Z., Floudas, C. S., Chen, F., Gong, C., Bracken-Clarke, D., Xue, E., Yang, Y., Sun, J., & Lu, Z. (2024) · Nature Communications

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 287

Matching Patients to Clinical Trials with Large Language Models

Jin, Q., Wang, Z., Floudas, C. S., Chen, F., Gong, C., Bracken-Clarke, D., Xue, E., Yang, Y., Sun, J., & Lu, Z. (2023) · arXiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 287

Artificial intelligence foundation for therapeutic science

Huang, K., Fu, T., Gao, W., Zhao, Y., Roohani, Y., Leskovec, J., Coley, C. W., Xiao, C., Sun, J., & Zitnik, M. (2022) · Nature Chemical Biology

Computational Drug Discovery MethodsArtificial Intelligence in Healthcare and Education

Cited by 207

Privacy-Preserving Patient Similarity Learning in a Federated Environment: Development and Analysis

Lee, J., Sun, J., Wang, F., Wang, S., Jun, C.-H., & Jiang, X. (2018) · JMIR Medical Informatics

Privacy-Preserving Technologies in DataMachine Learning in Healthcare

Cited by 196

Hierarchical Reinforcement Learning for Course Recommendation in MOOCs

Zhang, J., Hao, B., Chen, B., Li, C., Chen, H., & Sun, J. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence

Recommender Systems and TechniquesOnline Learning and Analytics

Cited by 196

RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data

Xu, Y., Biswal, S., Deshpande, S. R., Maher, K. O., & Sun, J. (2018) · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Machine Learning in HealthcareHealthcare Technology and Patient Monitoring

Cited by 144

SkipGNN: predicting molecular interactions with skip-graph networks

Huang, K., Xiao, C., Glass, L. M., Zitnik, M., & Sun, J. (2020) · Scientific Reports

Bioinformatics and Genomic NetworksComputational Drug Discovery Methods

Cited by 133

Federated Tensor Factorization for Computational Phenotyping

Kim, Y., Sun, J., Yu, H., & Jiang, X. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Privacy-Preserving Technologies in DataMachine Learning in Healthcare

Cited by 128

Fast Random Walk Graph Kernel

Kang, U., Tong, H., & Sun, J. (2012) · Proceedings of the 2012 SIAM International Conference on Data Mining

Graph Theory and AlgorithmsAdvanced Graph Neural Networks

Cited by 127

MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models

Wen, Y., Wang, Z., & Sun, J. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 113

MindMap: Knowledge graph prompting sparks graph of thoughts in large language models

Wen, Y., Wang, Z., & Sun, J. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingMultimodal Machine Learning Applications

Cited by 113

Characterizing the clinical adoption of medical AI devices through U.S. insurance claims

Wu, K., Wu, E., Theodorou, B., Liang, W., Mack, C., Glass, L., Sun, J., & Zou, J. (2024) · NEJM AI

Artificial Intelligence in Healthcare and EducationHealthcare Policy and Management

Cited by 103

DRG-LLaMA : tuning LLaMA model to predict diagnosis-related group for hospitalized patients

Wang, H., Gao, C., Dantona, C., Hull, B., & Sun, J. (2024) · npj Digital Medicine

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 99