Weiner, Mark G.
7 papers on CoChatORCID 0000-0001-5586-9940
Most cited papers
- Verified
Caveats for the Use of Operational Electronic Health Record Data in Comparative Effectiveness Research
Hersh, W. R., Weiner, M. G., Embi, P. J., Logan, J. R., Payne, P. R. O., Bernstam, E. V., Lehmann, H. P., Hripcsak, G., Hartzog, T. H., Cimino, J. J., et al. (2013) · Medical Care
Electronic Health Records SystemsMedical Coding and Health Information
Cited by 567
- Verified
Toward a responsible future: recommendations for AI-enabled clinical decision support
Labkoff, S., Oladimeji, B., Kannry, J., Solomonides, A., Leftwich, R., Koski, E., Joseph, A. L., Lopez-Gonzalez, M., Fleisher, L. A., Nolen, K., et al. (2024) · Journal of the American Medical Informatics Association
Artificial Intelligence in Healthcare and EducationElectronic Health Records Systems
Cited by 252
- Verified
Extracting social determinants of health from electronic health records using natural language processing: a systematic review
Patra, B. G., Sharma, M. M., Vekaria, V., Adekkanattu, P., Patterson, O. V., Glicksberg, B., Lepow, L. A., Ryu, E., Biernacka, J. M., Furmanchuk, A., et al. (2021) · Journal of the American Medical Informatics Association
Machine Learning in HealthcareBiomedical Text Mining and Ontologies
Cited by 248
- Verified
Toward Reuse of Clinical Data for Research and Quality Improvement: The End of the Beginning?
Weiner, M. G., & Embi, P. J. (2009) · Annals of Internal Medicine
Electronic Health Records SystemsMedical Coding and Health Information
Cited by 129
- Verified
Visits to Physicians after the Oxygenation of Gasoline in Philadelphia
Joseph, P. M., & Weiner, M. G. (2002) · Archives of Environmental Health: An International Journal
Air Quality and Health ImpactsIndoor Air Quality and Microbial Exposure
Cited by 17
- Verified
Deep learning for identifying personal and family history of suicidal thoughts and behaviors from EHRs
Adekkanattu, P., Furmanchuk, A., Wu, Y., Pathak, A., Patra, B. G., Bost, S., Morrow, D., Wang, G. H.-M., Yang, Y., Forrest, N. J., et al. (2024) · npj Digital Medicine
Machine Learning in HealthcareMental Health via Writing
Cited by 12
- Verified
Developing a computable phenotype for identifying children, adolescents, and young adults with diabetes using electronic health records in the DiCAYA Network.
Shao, H., Thorpe, L. E., Islam, S., Bian, J., Guo, Y., Li, P., Bost, S., Dabelea, D., Conway, R., Crume, T., et al. (2025) · Diabetes Care
Machine Learning in HealthcareMedical Coding and Health Information
Cited by 8
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