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SUMMARY:Cambridge AI in Medicine Seminar - July 2026 - Mengling Feng and K
 ai He
DTSTART:20260709T104500Z
DTEND:20260709T120000Z
UID:TALK246025@talks.cam.ac.uk
CONTACT:Hannah Clayton
DESCRIPTION:Sign up on Eventbrite: link to follow\n\nJoin us for the *Camb
 ridge AI in Medicine Seminar Series*\, hosted by the *Cancer Research UK C
 ambridge Centre* and the *Department of Radiology at Addenbrooke’s*. Thi
 s series brings together leading experts to explore cutting-edge AI applic
 ations in healthcare – from disease diagnosis to drug discovery. It’s 
 a unique opportunity for researchers\, practitioners\, and students to sta
 y at the forefront of AI innovations and engage in discussions shaping the
  future of AI in healthcare.\n\nThis month’s seminar will be held on *Th
 ursday 9 July 2026\, 12-1pm at the Jeffrey Cheah Biomedical Centre (Main L
 ecture Theatre)\, University of Cambridge* and *streamed online via Zoom*.
  A light lunch from Aromi will be served from 11:45. The event will featur
 e the following talks:\n\n*_When AI meets health and public health: from c
 omputer vision to LLMs to agentic AIs_ - Mengling 'Mornin' Feng\, Associat
 e Professor at National University of Singapore\,  Director of AI for Publ
 ic Health Center*\n\n*Abstract*: The rapid evolution of artificial intelli
 gence is reshaping both clinical medicine and public health at an unpreced
 ented pace. This talk traces our lab's development journey of AI in health
 care — from early breakthroughs in computer vision for medical imaging a
 nalysis\, through the transformative potential of large language models (L
 LMs) in clinical text processing and decision support\, to the emerging fr
 ontier of agentic AI systems capable of autonomous reasoning and action in
  complex healthcare environments. Drawing on real-world research and appli
 cations\, we explore how each wave of AI innovation has unlocked new possi
 bilities for disease detection\, treatment recommendation\, and population
  health management. We also examine the unique challenges that arise as AI
  systems become more autonomous\, including issues of trust\, safety\, and
  equity in diverse healthcare settings.\n\n*_Building Closed-Loop LLM Syst
 ems for Scalable Mental Health Support_ - Kai He\, Senior Research Fellow\
 , Saw Swee Hock School of Public Health\, National University of Singapore
 *\n\n*Abstract*: Mental health systems worldwide are under growing strain\
 , with increasing demand for early support and limited specialist capacity
 . While large language models (LLMs) have shown promise in conversational 
 mental health applications\, most existing systems operate as static chatb
 ots without structured assessment\, longitudinal monitoring\, or calibrate
 d escalation mechanisms. This talk presents a closed-loop LLM framework de
 signed to support scalable mental health care rather than isolated convers
 ational assistance. The system integrates empathetic dialogue generation w
 ith continuous state assessment\, structured rubric-based evaluation\, and
  reinforcement-driven improvement. A multi-agent architecture enables iter
 ative feedback between support generation and risk evaluation\, forming a 
 dynamic loop that mirrors stepped-care principles in public health.\n\nThi
 s is a hybrid event so you can also join via Zoom: https://zoom.us/j/99050
 467573?pwd=UE5OdFdTSFdZeUtIcU1DbXpmdlNGZz09\n\nMeeting ID: 990 5046 7573 a
 nd Passcode: 617729\n\nWe look forward to your participation! If you are i
 nterested in getting involved and presenting your work\, please email Ines
  Machado at im549@cam.ac.uk\n\nFor more information about this seminar ser
 ies\, see: https://www.integratedcancermedicine.org/research/cambridge-med
 ai-seminar-series/
LOCATION:Jeffrey Cheah Biomedical Centre (Main Lecture Theatre)\, Universi
 ty of Cambridge
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