AI.Health4All Research

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Chicago Data-driven Opioid Screening, Evaluation, Treatment and Prevention (C-DOSETaP) Program

Principal Investigator:
Niranjan S. Karnik , MD, PhD
Department of Psychiatry, Chicago

Machine Learning Approaches for the Detection of Emergency Department Patients with Opioid Misuse

Principal Investigator:
Neeraj Chhabra, MD, MSCR
Department of Emergency Medicine, Chicago

Postdoctoral Fellow:
Chirag Chhablani, PhD

Exploring the Efficacy of AI Tools in Monitoring Mental Illnesses Through Social Media Engagement

Investigator:
Ranga Chandrasekaran
Department of Information & Decision Sciences

Virtual Experiences to Improve Health Equity

Investigator:
Mohan Zalake
Department of Biomedical and Health Information Sciences

Sustainably improve pediatric healthcare through data-driven research and digital innovation.

Investigator:
Adam Cross, MD, FAAP, FAMIA
Department of Pediatrics, Peoria

Postdoctoral Fellow:
Paul Landes, PhD

Utilize frontal chest radiography images (CXR) and AI in the form of convolutional neural network (CNN), we can accurately predict chronic disease (i.e. Type 2 diabetes).

Investigator:
Brian Layden, MD, PhD
Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Chicago

Postdoctoral Fellow:
Lydia Lagari, PhD

Develop and demonstrate how AI can help overcome current barriers to wider adoption of remote telesurgery to address health care resource disparities.

Investigator:
Liaohai Leo Chen, PhD; Neil Getty, PhD
Department of Surgery, Chicago; Argonne National Laboratory

Postdoctoral Fellow:
Hossein Haeri, PhD

Utilize AI and ML techniques to predict cancer incidence in patients by analyzing clinical and demographic features and leveraging radiomic features from CT chest radiographs.

Investigator:
Ameen Saludaheen, MD, PhD; Ryan Nguyen, DO
Division of Cardiology, Department of Medicine, Chicago; Division of Hematology and Oncology, Department of Medicine, Chicago

Postdoctoral Fellow:
Nazi Perwaiz, PhD

Design and implement AI-powered interventions to improve access to care and reduce disparities in health outcomes for our underserved communities enrolled in the Hospital-at-Home program.

Investigator:
Masahito Jimbo, MD, PhD, MPH, FAAFP; Anwar Jebran, MD
Department of Family & Community Medicine, Chicago

Postdoctoral Fellow:
Mohammad Arvan, PhD

Assess the needs, preferences, attitudes and potential barriers and facilitators of integrating AI into rural healthcare delivery.

Investigator:
Hana Hinkle, PhD, MPH
Department of Family & Community Medicine, Rockford

Postdoctoral Fellow:
Kiruthika Balakrishnan, PhD

Leverage AI tools to address health inequities and rural-urban health disparities.

Investigator:
Sunita Dodani, MBBS (MD), FCPS, MSc, PhD, FAHA
Department of Medicine, Peoria

Develop an AI-based method that performs equally well across different racial categories, with high accuracy, reversing the current well-documented racial disparity in Aortic Stenosis diagnosis.

Investigator:
Kamran Avanaki, PhD; Hema Krishna, MD; Mayan Kansal, MD
Biomedical Engineering, Chicago; Division of Cardiology, Department of Medicine, Chicago

Postdoctoral Fellow:
Chris Sevastopoulos, PhD

Utilize AI to improve imaging systems to better identify melanoma in diverse populations.

Investigator:
Maria Tsoukas, MD, PhD
Department of Dermatology, Chicago

Create a new generative AI model to analyze RPM data and researching experimental clinical workflows to provide equitable solutions for blood pressure control.

Investigator:
Karl Kochendorfer, MD, FAAFP, FAMIA
Department of Family & Community Medicine, Chicago

Chest X-Ray AI for Early Detection and Risk Assessment of Lung Cancer in Smoking Populations in the VA

Investigator:
Darvin Yi, PhD
Department of Ophthalmology and Visual Sciences, Chicago

Generate robust early feedback signals for minoritized trainee groups using AI/ML techniques.

Investigator:
Yoon Soo Park, PhD
Department of Medical Education, Chicago

Develop a computable clinical phenotype algorithm to identify Ehlers-Danlos Syndrome and estimate a population prevalence.

Investigator:
Rebecca Feinstein, MPH, MSW, PhD
Department of Psychiatry, Chicago

Utilize AI tools to uncover unique factors and circumstances that may influence their pre and post-transplant progression.

Investigator:
Jorge Almario Alvarez, MD
Department of Surgery, Chicago

Harnessing AI to Counter Medical Misinformation on Social Media