Health and Explainable AI Podcast cover art

Health and Explainable AI Podcast

Health and Explainable AI Podcast

By: Pitt HexAI Lab and the Computational Pathology and AI Center of Excellence
Listen for free

About this listen

The Health and Explainable AI podcast is a collaborative initiative between the Health and Explainable AI (HexAI) Research Lab in the Department of Health Information Management at the School of Health and Rehabilitation Sciences, and the Computational Pathology and AI Center of Excellence (CPACE), at the University of Pittsburgh School of Medicine. Led by Ahmad P. Tafti, Hooman Rashidi and Liron Pantanowitz, the podcast explores the transformative integration of responsible and explainable artificial intelligence into health informatics, clinical decision-making, and computational medicine.Pitt HexAI Lab and the Computational Pathology and AI Center of Excellence
Episodes
  • Jason Moore from Cedars-Sinai on the Incorporation of AI Agents into Precision Health
    Oct 14 2025

    Jason Moore, Chair of the Department of Computational Biomedicine and Director of the Center for Artificial Intelligence Research and Education (CAIRE) at Cedars-Sinai Medical Center in Los Angeles, CA, speaks with Pitt’s HexAI podcast host, Jordan Gass-Pooré, about his work, the strategic investments his center is making in technology and specialized human expertise to support advanced AI research and about the incorporation of AI and AI agents into precision health.

    They speak in depth about the recent and rapid emergence of agentic AI, which is expected to have a significant impact on healthcare and how his team’s work is advancing the field. They also touch on vetting, deploying, and monitoring AI models for clinical use; explainable AI, trust, and transparency; using AI chatbots to improve the patient experience; the importance of building effective collaborations between industry and academia; and Cedar-Sinai’s new PhD program in Health AI.

    Show More Show Less
    33 mins
  • Peter Maurer from the University of Chicago on the Future Impact of Quantum Sensing on Biomedical Research and Diagnostics
    Sep 10 2025

    Peter Maurer, Assistant Professor of Molecular Engineering at the University of Chicago Pritzker School of Molecular Engineering, speaks with Pitt’s HexAI podcast host, Jordan

    Gass-Pooré, about the future impact of quantum sensing on biomedical research and diagnostics.

    Peter's research lab leverages the extreme environmental sensitivity of quantum systems to develop powerful sensors suitable for cutting-edge biological research that are optically addressable and can operate under ambient conditions. He outlines both near-term and future applications of powerful quantum sensors in pathology and laboratory medicine. He provides a key example of how these sensors could enable a new type of nanoscale NMR spectroscopy, capable of measuring magnetic fields from biomolecules to non-invasively probe their chemical information and signaling pathways. In the near future, he points to diagnostic tools, currently being developed by companies, that use the unique optical signatures of quantum sensors for highly sensitive, background-free protein detection in small volumes. For the long term, he envisions the technology as a "field opener" for studying protein aggregation in neurodegenerative diseases like Alzheimer's and Parkinson’s.

    Peter outlines how AI can be applied to analyze complex data from sensors that respond to multiple environmental factors and highlights the challenge of bringing together experts from quantum technology, biophysics, and medicine who can "talk each other's language.” He also touches on how the use of synthetic data in quantum sensing is a "completely under-appreciated" area with the potential to analyze complex environmental properties that would otherwise be missed by looking at single types of measurements. To advance the field from academic proofs-of-concept to clinical tools, he stresses the need for collaboration with academic and industry partners who can help engineer robust, "turnkey" systems that can be widely tested and used.

    The University of Pittsburgh Health and Explainable AI podcast is a collaborative initiative between the Health and Explainable AI (HexAI) Research Laboratory in the Department of Health Information Management at the School of Health and Rehabilitation Sciences, and the Computational Pathology and AI Center of Excellence (CPACE), at the University of Pittsburgh School of Medicine.

    Hosted by Jordan Gass-Pooré, a health and science reporter, this podcast series explores the transformative integration of responsible and explainable artificial intelligence into health informatics, clinical decision-making, and computational medicine. From reshaping diagnostic accuracy to enhancing patient care pathways, we'll highlight how AI is creating new bridges between researchers, clinicians, and healthcare innovators.

    Led by Ahmad P. Tafti, Hooman Rashidi and Liron Pantanowitz, the HexAI podcast is committed to democratizing knowledge around ethical, explainable, and clinically relevant AI. Through insightful conversations with domain experts, AI practitioners and students will spotlight the latest breakthroughs, discuss real-world applications, and unpack the challenges and opportunities that lie ahead in responsible AI in healthcare. So whether you're a student, practitioner, researcher, or policymaker, this is your gateway to the future of AI-powered healthcare

    Show More Show Less
    26 mins
  • Karen Colbert on Pitt HexAI
    Jun 5 2025

    Karen Colbert, an AI strategist, data scientist, and Lead Math Faculty at Keweenaw Bay Ojibwa Community College, speaks with Pitt HexAI Producer, Brent Phillips about tribal colleges and their mission and vision to revitalize language and culture through education, the indigenization of math and teaching math, computing and data science in the AI age, collaboration tools, data sharing and privacy, explainability and storytelling, project ideation, AI applications, data annotation, and life lessons for students.


    Karen Colbert is an AI strategist, data scientist, keynote speaker, and a nationally recognized advocate for STEM education. She currently serves as the General Education Department Chair and Lead Math Faculty at Keweenaw Bay Ojibwa Community College, a Tribal College, where she advances data and computational literacy for Indigenous students. Notably, Karen became the first Data Carpentries Instructor and Trainer among all Tribal Colleges, pioneering efforts to bridge the digital divide in higher education. Her passion lies in ensuring that non-traditional, re-entry, and adult learners are not left behind in the AI revolution. Karen is passionate about sharing her insights on “digital sovereignty in the age of AI.” Specifically, she has a deep interest in exploring how AI is reshaping education, research, and opportunity, challenging educators to lead with cultural integrity as technology evolves.


    She also has an upcoming book 'The Algorithm wasn't Built for Us: Reclaiming the Future of AI, Education, and Culture' available July 4 on Amazon. Visit her website: https://www.karencolbert.com/

    Show More Show Less
    49 mins
No reviews yet
In the spirit of reconciliation, Audible acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.