A photo of Judith Dexheimer.

Judith W. Dexheimer, PhD

  • Associate Professor, UC Department of Pediatrics



The ultimate goal of my research is to harness technology to improve healthcare delivery and the quality of care for children. My research interests include machine learning (ML), decision support, personal health records and multi-center informatics implementations. During my National Library of Medicine (NLM) informatics training, I studied artificial intelligence and implemented reminder systems directly into clinical care in the adult and pediatric emergency departments. My goals are to improve disease detection, especially earlier disease detection, for patients with a long history of illness. I also want to provide technology and healthcare information to underserved populations, improve care delivery and help providers use the computer as a tool that incorporates ML directly into clinical care.

I see myself accomplishing this goal by designing ways to use ML to enhance the patient-clinician experience at the point of care and by improving patient interactions with health technology in and outside of the healthcare encounter.

I was drawn to this field of research after seeing well-designed ML algorithms created but not integrated into clinical care. I also noticed that patients frequently did not have access to their own healthcare data.

Working with a collaborative team, we want to improve the use of informatics. I have experience in designing, implementing and evaluating clinical information systems, including clinical decision support systems, computerized applications for emergency medicine, organizational and workflow aspects of informatics applications.

A few of my accomplishments include:

  • Collaborating with the Pestian lab to develop one of the first real-time integrations of machine learning (epilepsy classifier) into clinical care
  • Working with Dr. Yizhao Ni at Cincinnati Children’s to integrate an automated ML patient screening system into the pediatric emergency department
  • Collaborating with Mary Greiner (Mayerson Center for Safe and Healthy Children) and Sarah Beal (Behavioral Medicine and Clinical Psychology) to develop the IDENTITY platform to share data more efficiently between the hospital and Hamilton county job and family services caseworkers, including automated matching of patients in custody

I was nominated for the Presidential Early Career Awards for Scientists and Engineers (PECASE) in 2017 and invited as a presenter at the Amazon Web Services (AWS) Machine Learning Summit in 2019. I have been a researcher for over nine years and began my work at Cincinnati Children’s in 2011.


The Risk of Coding Racism into Pediatric Sepsis Care: The Necessity of Antiracism in Machine Learning. Sveen, W; Dewan, M; Dexheimer, JW. Journal of Pediatrics. 2022; 247:129-132.

Diversity in Machine Learning: A Systematic Review of Text-Based Diagnostic Applications. Fitzsimmons, L; Dewan, M; Dexheimer, JW. Applied Clinical Informatics. 2022; 13:569-582.

Implementation of Machine Learning Pipelines for Clinical Practice (Preprint). Kanbar, L; Wissel, B; Ni, Y; Pajor, N; Glauser, T; Pestian, J; Dexheimer, J. JMIR Medical Informatics. 2022.

Aligning Provider Prescribing With Guidelines for Soft Tissue Infections. Kovaleski, C; Courter, JD; Ghulam, E; Hagedorn, PA; Haslam, DB; Kurowski, EM; Rudloff, J; Szczesniak, R; Dexheimer, JW. Pediatric Emergency Care. 2022; 38:e1063-e1068.

An ontology-based review of transgender literature: Revealing a history of medicalization and pathologization. Kronk, CA; Dexheimer, JW. International Journal of Medical Informatics. 2021; 156.

Early identification of epilepsy surgery candidates: A multicenter, machine learning study. Wissel, BD; Greiner, HM; Glauser, TA; Pestian, JP; Kemme, AJ; Santel, D; Ficker, DM; Mangano, FT; Szczesniak, RD; Dexheimer, JW. Acta Neurologica Scandinavica. 2021; 144:41-50.

Effectiveness of a Universally Offered Chlamydia and Gonorrhea Screening Intervention in the Pediatric Emergency Department. Reed, JL; Alessandrini, EA; Dexheimer, J; Kachelmeyer, A; Macaluso, M; Zhang, N; Kahn, JA. Journal of Adolescent Health. 2021; 68:57-64.

Utilization of a Clinical Decision Support Tool to Reduce Child Tobacco Smoke Exposure in the Urgent Care Setting. Mahabee-Gittens, EM; Merianos, AL; Dexheimer, JW; Meyers, GT; Stone, L; Tabangin, M; Khoury, JC; Gordon, JS. Pediatric Emergency Care. 2020; 36:527-531.

Information Technology-Assisted Screening for Gonorrhea and Chlamydia in a Pediatric Emergency Department. Reed, JL; Dexheimer, JW; Kachelmeyer, AM; Macaluso, M; Alessandrini, EA; Kahn, JA. Journal of Adolescent Health. 2020; 67:186-193.

Feedback at the Point of Care to Decrease Medication Alert Rates in an Electronic Health Record. van Camp, PJ; Kirkendall, ES; Hagedorn, PA; Minich, T; Kouril, M; Spooner, SA; Gecili, E; Dexheimer, JW. Pediatric Emergency Care. 2020; 36:e417-e422.