Charles Friedman hosts our March Seminar Series
March 5, 2025
We were thrilled to welcome Charles Friedman from the University of Michigan Medical School,
who delivered our March Seminar Series with his talk,
"Why AI and Learning Health Systems Need Each Other".
Charles began by advancing the idea that, while both are extremely important: AI is a means and Learning Health Systems (LHS) are an end--and why it is most important to maintain that distinction. He introduced the socio-technical infrastructure required for high-functioning learning systems and argue that this infrastructure provides a framework, actually a schematic, for successfully implementing AI into healthcare.
Charles Friedman is Professor of Learning Health Sciences at the University of Michigan Medical School, where he directs the Knowledge Systems Laboratory. He was formerly Founding Chair of the Department of Learning Health Sciences and the Josiah Macy Jr. Professor of Medical Education. He holds joint appointments in the Schools of information and Public Health. He is editor-in-chief of the open-access journal Learning Health Systems and co-chair of the multi-national movement to Mobilize Computable Biomedical Knowledge.
Throughout his career, Friedman has developed and studied methods to improve health, education, and research through innovative applications of information technology. Most recently, Friedman has focused his academic interests and activities on the concept of Learning Health Systems that improve health by marrying discovery to implementation, and the socio-technical infrastructure required to sustain these systems.
Friedman is a Distinguished Fellow of the American College of Medical Informatics, and a founding fellow of the International Academy of Health Sciences Informatics. He holds an honorary doctorate from the University of Lucerne in Switzerland for his contributions to the science of Learning Health Systems. Prior to coming to Michigan, Friedman held executive positions at the Office of the National Coordinator for Health IT (ONC) in the U.S. Department of Health and Human Services. Immediately prior to his work in the government, he was Associate Vice Chancellor for Biomedical Informatics, and Founding Director of the Center for Biomedical Informatics at the University of Pittsburgh.
Seminar Series Event: "Why AI and Learning Health Systems Need Each Other"
Date and Time:
Wednesday 26 March 2025, 10:00 – 11.00 hrs (BST)
Location: The Anatomy Museum, King's Building, Room K6.36, Strand Campus, Strand, London, WC2R 2LS
Attendance:
Mandatory for all DRIVE-Health students, therefore please accept the calendar invitation.
Registration: Alumni and wider King's College London research community all welcome - please email
drive-health-cdt@kcl.ac.uk
to let us know if you would like to attend.
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We are looking forward to welcoming Professor Honghan Wu, Professor of Health Informatics and AI at the University of Glasgow, who will deliver his talk “Large language model and Radiology: how to facilitate human and AI collaboration? " as part of our Seminar Series. Abstract: In this upcoming talk, Professor Honghan Wu explores the essential shift from viewing AI as a potential replacement for radiologists to recognizing it as a critical collaborative partner. Moving beyond basic tasks like detection and triage, the presentation highlights how AI can address practical clinical "pain points," such as reducing automated protocoling time by up to 60% and decreasing the time spent communicating with providers and patients by 30%. Professor Wu will present recent research on using knowledge-retrieval and Large Language Models for clinical report error correction and generation. The session concludes with an examination of the real-world deployment lifecycle, discussing the challenges of monitoring the over 700 FDA-cleared radiology AI devices currently in practice Seminar Series Event : “Large language model and Radiology: how to facilitate human and AI collaboration?" Date and Time: Thursday 25 November 2026, 15:00 – 16.00 hrs (GMT) Location: Venue to be confirmed. Attendance: Mandatory for all DRIVE-Health students; a calendar invitation has already been sent. Registration: Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend. Biography Honghan Wu is a Professor of Health Informatics and AI, based in the School of Health and Wellbeing of the University of Glasgow, where he leads the research theme of data science and AI. Prof Wu is a co-director of Health Data Research Scotland. He also is an honorary professor at Hong Kong University, an honorary associate professor at Institute of Health Informatics, UCL, and a former Turing Fellow of The Alan Turing Institute, UK's national institute for data science and artificial intelligence. Prof Wu holds a PhD in Computing Science. His current research focuses on machine learning, natural language processing, knowledge graph and their applications in medicine.
We are looking forward to welcoming Dr. Bettina Moltrecht and Thomas Wood to introduce Harmony Meta , a groundbreaking platform developed over the past year to bridge the gap between disparate study catalogues and registers. While traditional data discovery relies on exact keyword matching, Harmony Meta utilizes Large Language Models and vector indexing to allow for semantic searching across 5.5 million variables . Abstract: This session will demonstrate how researchers can now locate longitudinal data using approximate synonyms—for instance, a search for "dyslexia" will successfully retrieve variables related to "difficulty reading." The platform indexes nearly every major longitudinal study ever conducted in the UK, including the Millennium Cohort Study , the 1970 British Cohort Study , and Born in Bradford . The presenters will discuss the technical backend of converting millions of variables into vectors and the practical implications for harmonizing data across different cohorts to identify population mental health trends. Try the Tool: https://harmonydata.ac.uk/search Seminar Series Event : " Harmony Meta: Using AI to Unlock 5.5 Million Variables in UK Longitudinal Studies" Date and Time: Thursday 24 September 2026, 15:00 – 16.00 (BST) Location: Venue to be confirmed. Attendance: Mandatory for all DRIVE-Health students; a calendar invitation has already been sent. Registration: Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend. Biographies Dr. Bettina Moltrecht Dr. Bettina Moltrecht is a mental health researcher based at University College London (UCL) and Anna Freud a UK-based mental health charity for children and families. Bettina combines a clinical, tech and research background, and has been co-leading the Harmony project with the aim to enhance population mental health research. Bettina is co-founder of UCL's Digital Mental Health Hub, and is co-investigator on various clinical trials to evaluate mental health interventions in the NHS. Thomas Wood Thomas Wood is the founder of Fast Data Science and the lead developer for the Harmony Meta backend. He holds a Master’s in Physics from Durham University and a Master’s in Computer Speech, Text and Internet Technology from the University of Cambridge. With over a decade of experience in machine learning and NLP, Thomas has consulted for the NHS, Tesco, and Boehringer Ingelheim. He also works as an expert witness and is working on NLP solutions for clinical trials, and generative AI solutions for legal question answering. Note on Funding and Partners: Harmony Meta was funded by the ESRC and developed in collaboration with Population Research UK (PRUK), the UCL Centre for Longitudinal Studies, DATAMIND UK, The Alan Turing Institute, and UK Research and Innovation.
