Elhadad, Noémie

Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants

Pratap, A., Neto, E. C., Snyder, P., Stepnowsky, C., Elhadad, N., Grant, D., Mohebbi, M. H., Mooney, S., Suver, C., Wilbanks, J., et al. (2020) · npj Digital Medicine

Mobile Health and mHealth ApplicationsEthics in Clinical Research

Cited by 410

Diagnosis code assignment: models and evaluation metrics

Perotte, A., Pivovarov, R., Natarajan, K., Weiskopf, N., Wood, F., & Elhadad, N. (2014) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 244

HARVEST, a longitudinal patient record summarizer

Hirsch, J. S., Tanenbaum, J. S., Lipsky Gorman, S., Liu, C., Schmitz, E., Hashorva, D., Ervits, A., Vawdrey, D., Sturm, M., & Elhadad, N. (2015) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsData Visualization and Analytics

Cited by 135

Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment

Feller, D. J., Zucker, J., Yin, M. T., Gordon, P., & Elhadad, N. (2018) · JAIDS Journal of Acquired Immune Deficiency Syndromes

Machine Learning in HealthcareHIV/AIDS Research and Interventions

Cited by 130

Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis

Perotte, A., Ranganath, R., Hirsch, J. S., Blei, D., & Elhadad, N. (2015) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareChronic Kidney Disease and Diabetes

Cited by 128

Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies

Cohen, R., Elhadad, M., & Elhadad, N. (2013) · BMC Bioinformatics

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 121

Identifying and mitigating biases in EHR laboratory tests

Pivovarov, R., Albers, D. J., Sepulveda, J. L., & Elhadad, N. (2014) · Journal of Biomedical Informatics

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 91

Detecting Social and Behavioral Determinants of Health with Structured and Free-Text Clinical Data

Feller, D. J., Bear Don't Walk IV, O. J., Zucker, J., Yin, M. T., Gordon, P., & Elhadad, N. (2020) · Applied Clinical Informatics

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 86

Redundancy-Aware Topic Modeling for Patient Record Notes

Cohen, R., Aviram, I., Elhadad, M., & Elhadad, N. (2014) · PLoS ONE

Machine Learning in HealthcareTopic Modeling

Cited by 71

Deep-Learning Approaches to Identify Critically Ill Patients at Emergency Department Triage Using Limited Information

Joseph, J. W., Leventhal, E. L., Grossestreuer, A. V., Wong, M. L., Joseph, L. J., Nathanson, L. A., Donnino, M. W., Elhadad, N., & Sanchez, L. D. (2020) · Journal of the American College of Emergency Physicians Open

Machine Learning in HealthcareEmergency and Acute Care Studies

Cited by 57

Temporal trends of hemoglobin A1c testing

Pivovarov, R., Albers, D. J., Hripcsak, G., Sepulveda, J. L., & Elhadad, N. (2014) · Journal of the American Medical Informatics Association

Healthcare cost, quality, practicesClinical Laboratory Practices and Quality Control

Cited by 41

Machine learning to extract communication and history‐taking skills in OSCE transcripts

Jani, K. H., Jones, K. A., Jones, G. W., Amiel, J., Barron, B., & Elhadad, N. (2020) · Medical Education

Innovations in Medical EducationArtificial Intelligence in Healthcare and Education

Cited by 39

Comparing evaluation techniques for text readability software for adults with intellectual disabilities

Huenerfauth, M., Feng, L., & Elhadad, N. (2009) · Proceedings of the 11th international ACM SIGACCESS conference on Computers and accessibility

Text Readability and SimplificationDigital Accessibility for Disabilities

Cited by 35

Representing and utilizing clinical textual data for real world studies: An OHDSI approach

Keloth, V. K., Banda, J. M., Gurley, M., Heider, P. M., Kennedy, G., Liu, H., Liu, F., Miller, T., Natarajan, K., V Patterson, O., et al. (2023) · Journal of Biomedical Informatics

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 16