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SCHOLAR Project

In Collaboration with Sinai Urban Health Institute

SCHOLAR (Smart, Connected, and Healthy Outcomes from Leveraging Assets and Research) aims to enhance community health programs by integrating emerging technologies. Focused on under-resourced neighborhoods in Chicago, the project partners with Sinai Chicago to strengthen the connection between Community Health Workers (CHWs) and health systems.

The SCHOLAR project aims to design, develop, and evaluate a smart dashboard that will empower CHWs to interact with and interpret data leading to improved computational prediction modeling for Emergency Department (ED) readmission rates, improved health system risk stratification and resource allocation, and strengthening of the smart connection between the health system and the communities it serves.

This research is supported by the National Science Foundation (NSF) under grant number 2326676.

For more information on the project, contact the Principal Investigator (PI) Dr. Daniela Stan Raicu.

People

Faculty

Students

  • Ankita Mishra, MS Data Science
  • Minh Nguyen, BS Data Science
  • Charmi Patel, PhD Computer Vision
  • Binita Saha, Postdoctoral Researcher

Publications

  • Shah J., Musale S., Mishra A., Maglani N., Furst J., Raicu D., Mazzeo J., Chestnut A., Kidambi A., Bucio R., Banks M., Seals G., McCabe K., Tchoua R., "Harnessing Machine Learning to Optimize Community Health Worker Interventions for High-Risk Patients". 41st International Conference on Computers and Their Applications (CATA 2026), Honolulu, Hawaii, March 23-25, 2026
  • Mishra A., Patel C., Veeramreddy N. K. R., Wang Y., Mazzeo J., Sourati J., McCabe K., Tchoua R., Furst JD., Raicu DS., "Boosting 30-Day Emergency Department Readmission Predictions with BERT-Powered Community Health Worker Notes". 19th International Conference on Health Informatics, Marbella, Spain, March 2-4, 2026
  • Mishra A., Patel C., Maglani N., McCabe K., Tchoua R., Furst JD., Raicu DS., "From Notes to Needs: Extracting SDoH from CHW Narratives with NLP". American Medical Informatics Association (AMIA) Symposium , Atlanta, Georgia, November 15–19, 2025
  • Hernandez N., Karam K., Baugh N., Musale S., Mosca A.P., Raicu DS., Furst JD., McCabe K., Tchoua R., 'Leveraging Community Health Workers for Predicting Emergency Department Readmissions'. International Journal of Semantic Computing, 2024
  • Karam K., McCabe K., Tchoua R.,'Leveraging Community Health Workers and Social Determinants of Health for Predicting Emergency Department Readmissions'. Fifth International Conference on Transdisciplinary AI (TransAI), 2023
  • Veeramreddy N. K. R., Mishra A., Maglani N., Shaik S., McCabe K., Furst JD., Raicu DS., Tchoua R., Sourati J., 'Leveraging hidden patterns in open-ended health worker notes to improve prediction'. 21st IEEE International Conference on eScience , Chicago, Illinois, September 15-18, 2025

Activities

  • Focus Groups

    • Focus Groups aim to gather detailed insights and feedback from CHWs on various aspects of patient engagement and readmission. This would help us understand what factors contribute to patient engagement, identify key data points for predicting readmission, and pinpoint which factors are essential for follow-up care.

  • Educational Workshops for CHWs

    • The workshops are designed to provide Community Health Workers (CHWs) with essential data science skills and knowledge. They cover topics like data integration, preprocessing, selection, modeling, and evaluation. Additionally, these sessions focus on fostering collaboration between CHWs and technology to refine predictive models and create connected, community-driven solutions.

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