Roberts, Kirk

Enhancing clinical concept extraction with contextual embeddings

Si, Y., Wang, J., Xu, H., & Roberts, K. (2019) · Journal of the American Medical Informatics Association

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 322

Improving large language models for clinical named entity recognition via prompt engineering

Hu, Y., Chen, Q., Du, J., Peng, X., Keloth, V. K., Zuo, X., Zhou, Y., Li, Z., Jiang, X., Lu, Z., et al. (2024) · Journal of the American Medical Informatics Association

Topic ModelingBiomedical Text Mining and Ontologies

Cited by 314

Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review

Si, Y., Du, J., Li, Z., Jiang, X., Miller, T., Wang, F., Jim Zheng, W., & Roberts, K. (2021) · Journal of Biomedical Informatics

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 235

Scholarly recommendation systems: a literature survey

Zhang, Z., Patra, B. G., Yaseen, A., Zhu, J., Sabharwal, R., Roberts, K., Cao, T., & Wu, H. (2023) · Knowledge and Information Systems

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 73

Benefits of, Barriers to, and Needs for an Artificial Intelligence–Powered Medication Information Voice Chatbot for Older Adults: Interview Study With Geriatrics Experts

Gudala, M., Ross, M. E. T., Mogalla, S., Lyons, M., Ramaswamy, P., & Roberts, K. (2022) · JMIR Aging

Technology Use by Older AdultsArtificial Intelligence in Healthcare and Education

Cited by 71

A dataset of 200 structured product labels annotated for adverse drug reactions

Demner-Fushman, D., Shooshan, S. E., Rodriguez, L., Aronson, A. R., Lang, F., Rogers, W., Roberts, K., & Tonning, J. (2018) · Scientific Data

Pharmacovigilance and Adverse Drug ReactionsBiomedical Text Mining and Ontologies

Cited by 68

A flexible framework for recognizing events, temporal expressions, and temporal relations in clinical text

Roberts, K., Rink, B., & Harabagiu, S. M. (2013) · Journal of the American Medical Informatics Association

Biomedical Text Mining and OntologiesNatural Language Processing Techniques

Cited by 45

Distributed learning from multiple EHR databases: Contextual embedding models for medical events

Li, Z., Roberts, K., Jiang, X., & Long, Q. (2019) · Journal of Biomedical Informatics

Machine Learning in HealthcarePrivacy-Preserving Technologies in Data

Cited by 44

Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics

Roberts, K., Boland, M. R., Pruinelli, L., Dcruz, J., Berry, A., Georgsson, M., Hazen, R., Sarmiento, R. F., Backonja, U., Yu, K.-H., et al. (2017) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsArtificial Intelligence in Healthcare and Education

Cited by 25

Addressing ethical issues in healthcare artificial intelligence using a lifecycle-informed process

Collins, B. X., Bélisle-Pipon, J.-C., Evans, B. J., Ferryman, K., Jiang, X., Nebeker, C., Novak, L., Roberts, K., Were, M., Yin, Z., et al. (2024) · JAMIA Open

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 21

LLM-IE: a python package for biomedical generative information extraction with large language models

Hsu, E., & Roberts, K. (2025) · JAMIA Open

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 16

A dataset of chest X-ray reports annotated with Spatial Role Labeling annotations

Datta, S., & Roberts, K. (2020) · Data in Brief

Biomedical Text Mining and OntologiesMultimodal Machine Learning Applications

Cited by 14