» Research Center: Women in AI Healthcare Initiative

The Women in AI Healthcare Initiative (WAHI) at Chapman University highlights researchers using AI to address healthcare needs in Orange County, including geriatrics, opioid misuse, physical therapy, and drug delivery.

WAHI aims to promote equity in AI research and foster innovative solutions to improve healthcare outcomes and patient safety. Our goal is to connect and share ideas to advance the future of AI in healthcare by connecting with researchers both inside healthcare systems and those using AI for purposes outside of health systems.

Key healthcare drives of WAHI are to acknowledge the importance of ethical AI and algorithmic biases within Clinical Decision Support (CDS) tools, to develop ethical machine learning algorithms, and to ensure the privacy-preserving exchange of machine learning models.

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AI Enhances Patient Care:

Stories from our Newsroom

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AI Viable Alternative to Traditional Drug Discovery Process

AI and machine learning enable pre-synthesis molecule testing, offering improvements in cost, speed, and experimental integrity over traditional high throughput screening (HTS) methods. HTS, a standard in pharmaceutical development, identifies bioactive small molecules but requires testing before synthesis. A study published in Nature Scientific Reports demonstrated the effectiveness of deep learning-based methods, particularly the AtomNet model, in identifying promising drug-like hits for various pharmaceutical targets, highlighting the potential for a paradigm shift in drug discovery through computational techniques.

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Recent Grants

How AI/ML models in CDS tools for Opioid Prescribing Influence Inequalities in Patient Care

The NIH has awarded $250,000 to Dr. Wang, Dr. Wen, and Mr. Portillo to investigate potential biases in AI and machine learning systems used to treat patients with opioid use disorder.

Precision Medicine Approach to Identify Walking Phenotypes and Rehabilitation After Injury

Dr. Sánchez serves as the PI for NIH-funded research to enhance personalized rehabilitation by using machine learning to identify individual-specific walking phenotypes and their underlying joint and muscle impairments.

AI's Potential Macroeconomic Impacts and its Ability to Guide Microeconomic Choice

The Sloan Foundation awarded $250,000 over the span of three years to investigate AI's impact on the economy, including household labor and saving decisions. Dr. Benzell serves as the Co-PI.

Identifying and Remediating Algorithmic Bias in Opioid Overdose Risk Scores

The McGovern Foundation has awarded Dr. Wang and Dr. Wen for their project "Advancing Equity and Transparency in AI: Identifying and Remedying Algorithmic Bias in Opioid Overdose Risk Scores to Improve Access to Opioid Analgesics for Patients."

Recent Publication Highlights


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  • Women of WAHI
  • Senior Advisors
  • Members
  • Student Researchers
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    Anna Alber
    Senior Research Scientist
    • Recent projects: Supporting Linux-based hardware platforms has been instrumental in medical neuroimaging research endeavors.
    • Use of AI: Developing machine learning algorithms for neuroimaging.
    • Advice and advocacy for AI: Coming soon
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    Dr. Amy Kang
    Assistant Professor, School of Pharmacy
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Dr. Jillian Warren
    Assistant Professor, Wilkinson College of Arts, Humanities, and Social Sciences
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Dr. Moom Roosan
    Assistant Professor, School of Pharmacy
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Dr. Natalia Sánchez
    Assistant Professor, Crean College of Health and Behavioral Sciences
    • Recent projects: NIH R03 Grant: "A precision medicine approach to identify walking phenotypes and rehabilitation targets after injury."
    • Use of AI: Identify types of walking behaviors in pathological populations that could guide rehabilitation intervention prescription
    • Advice and advocacy for AI: "AI is most useful when done by a multidisciplinary team that can design rigorous pipelines, ensure quality and reproducibility, and inform on the appropriateness of analysis in a way that supports the phenomena under study. AI can always generate an output. It is up to the people who use AI to ensure the quality, rigor and significance of the output."
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    Dr. Jo Armour Smith
    Associate Professor, Crean College of Health and Behavioral Sciences
    • Recent projects: Using machine learning algorithms to better understand mechanisms underlying chronic low back pain
    • Use of AI: Identify clinically relevant phenotypes of individuals with back pain based on imaging, movement, and psychological data.
    • Advice and advocacy for AI: "My primary interest in AI is promoting clinically relevant use of tools that inform clinical decision-making and assist with developing new interventions for complex disorders such as chronic pain."
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    Dr. Sherry Wang
    Assistant Professor, School of Pharmacy
    • Recent projects:
      • PI on "Ethics and Equity in healthcare artificial intelligence (AI) application: Bias assessment in machine learning (ML) models for opioid prescribing". Award: $ 250,000. Agency: NIH's Artificial Intelligence/Machine Learning Consortium to AdvanceHealth Equity and Researcher Diversity (AIM-AHEAD) program
      • PI on "Advancing Equity and Transparency in AI: Identifying and Remedying Algorithmic Bias in Opioid Overdose Risk Scores to Improve Access to Opioid Analgesics for Patients". Award:$10,000; Agency: McGovern Foundation, McGovern Training Program in Trusted AI
    • Current research agenda: Explore the ethical implications of AI and machine learning in healthcare, emphasizing developing responsible AI solutions that ensure equitable access to healthcare resources, especially for patients with addiction and chronic diseases. 
    • Advice and advocacy for AI: AI can be sexist and racist —it’s time to make ethical AI in healthcare!
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    Dr. Yuxin Wen
    Assistant Professor, Fowler School of Engineering
    • Recent projects: Big data analysis, machine learning, and statistical modeling for quality improvement across various sectors, including healthcare.
    • Use of AI: Investigations into data-driven system fault detection, diagnosis, prognostics, as well as severity assessment and prediction of COVID-19 infection.
    • Advice and advocacy for AI: Coming soon
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    Dr. Cristina Giannantonio
    Professor, Argyros College of Business and Economics
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    Dr. Andrew Lyon
    Professor, School of Engineering and College of Science
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    Dr. Reginald Stewart
    Vice President of Diversity, Equity, and Inclusion
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    Dr. Rachita Sumbria
    Associate Professor, School of Pharmacy
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    Dr. Seth Benzell
    Assistant Professor, Argyros College of Business and Economics
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Micol Hebron
    Associate Professor, Wilkinson College of Arts, Humanities, and Social Sciences
    • Recent projects: History of the treatment of women's bodies as imagined by AI
    • Use of AI: Excavating gender bias and misogyny in AI text-to-image generators 
    • Advice and advocacy for AI: Coming soon
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    Lawrence Lau
    Director of Industry Alliances and Commercialization
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Phillip Lyle
    Deputy Chief Information Officer
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Luke O'Connell
    Marketing and Events Specialist, School of Pharmacy
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Ivan Portillo
    Director, Rinker Campus Library Services
    • Recent projects:
      • Publications of AI utilization in antimicrobial stewardship programs and using AI to identify potential international ASP programs
      • Instruction on the appropriate use of AI in relation to health information
    • Use of AI:
      • Considering keywords for literature searches and systematic reviews
      • Generative imagery
    • Advice and advocacy for AI:
      • Invest time to learn AI to complete simple tasks more efficiently  
      • Be wary of issues of hallucinations
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    Naveen Rajesh
    Statistical Research Programmer, School of Pharmacy
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Dr. Richard Ruppel
    Professor, Wilkinson College of Arts, Humanities, and Social Sciences
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Drake Watson
    Statistical Research Programmer
    • Recent projects: Coming soon
    • Use of AI: Coming soon
    • Advice and advocacy for AI: Coming soon
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    Adeola Bakare
    MS Pharmaceutical Sciences candidate
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    Ashley Duche
    PhD Pharmaceutical Sciences candidate
    • Current project: Leveraging bioinformatics tools for transcriptomics and gene expression analysis, aiming to reveal molecular mechanisms underlying various diseases. 
    • Use of AI: Compare the performances of statistical modeling and AI/ML for predicting disease outcomes.
    • Advice and advocacy for AI: Harnessing the power of AI and statistical modeling can drive transformative insights into disease progression and treatment. To maximize impact, focus on refining models for greater accuracy, interpretability, and clinical relevance, ensuring they lead to meaningful and actionable outcomes.
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    Melody Fewx
    PhD Pharmaceutical Sciences candidate
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    Silas Fernandes
    BA Psychology candidate
    Interests: Motivation and Emotion + Social Psychology, Human Sexuality, and Psychological Disorders
Contact Us
Primary Contact
Dr. Sherry Wang