A photo of Judith Dexheimer.

Associate Professor, UC Department of Pediatrics


Biography & Affiliation


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.

Research Interests

Learn more about the Decision Support Analytics Workgroup.

Academic Affiliation

Associate Professor, UC Department of Pediatrics


Biomedical Informatics, Emergency Medicine

Blog Posts


PhD: Biomedical Informatics, Vanderbilt University, Nashville, TN, 2011.

MS: Biomedical Informatics, Vanderbilt University, Nashville, TN, 2006.


Technological Hindrances of Behavioural Medicine Patient Access: A Literature Review. Rounds, J; Dexheimer, J; Curtis, H; Studebaker, B. 2020; 11:1-8.

Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery. Wissel, BD; Greiner, HM; Glauser, TA; Holland-Bouley, KD; Mangano, FT; Santel, D; Faist, R; Zhang, N; Pestian, JP; Szczesniak, RD; et al. Epilepsia. 2020; 61:39-48.

A Time-and-Motion Study of Clinical Trial Eligibility Screening in a Pediatric Emergency Department. Dexheimer, JW; Tang, H; Kachelmeyer, A; Hounchell, M; Kennebeck, S; Solti, I; Ni, Y. Pediatric Emergency Care. 2019; 35:868-873.

Automated patient linking for electronic health record and child welfare databases. Dexheimer, JW; Beal, SJ; Divekar, P; Hall, ES; Patel, V; Greiner, MV. Journal of Technology in Human Services. 2019; 37:286-292.

Investigation of bias in an epilepsy machine learning algorithm trained on physician notes. Wissel, BD; Greiner, HM; Glauser, TA; Mangano, FT; Santel, D; Pestian, JP; Szczesniak, RD; Dexheimer, JW. Epilepsia. 2019; 60:e93-e98.

Improving Information Sharing for Youth in Foster Care. Greiner, MV; Beal, SJ; Dexheimer, JW; Divekar, P; Patel, V; Hall, ES. Pediatrics. 2019; 144:e20190580-e20190580.

Sharing personal health record data elements in protective custody: Youth and stakeholder perspectives. Dexheimer, JW; Greiner, MV; Beal, SJ; Johnson, D; Kachelmeyer, A; Vaughn, LM. Journal of the American Medical Informatics Association. 2019; 26:714-721.

Designing and evaluating a real-time automated patient screening system in an emergency department. Ni, Y; Bermudez, M; Kennebeck, S; Liddy-Hicks, S; Dexheimer, J. Journal of Medical Internet Research. 2019; 7:e14185-e14185.

Mathematical Model for Computer-Assisted Modification of Medication Dosing Rules. Grabel, MZ; Vaughan, BL; Dexheimer, JW; Kirkendall, ES. Biomedical Informatics Insights. 2019; 11:1178222619829079-117822261982907.

The Parkinson's disease e-diary: Developing a clinical and research tool for the digital age. Vizcarra, JA; Sanchez-Ferro, A; Maetzler, W; Marsili, L; Zavala, L; Lang, AE; Martinez-Martin, P; Mestre, TA; Reilmann, R; Hausdorff, JM; et al. Movement Disorders. 2019; 34:676-681.