BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Harnessing Large Language Models for Medical Data Processing: Stru
 ctured Information Extraction\, Disease Classification\, and RAG Integrati
 on  - Cristian Cosentino (Università della Calabria)
DTSTART:20250225T170000Z
DTEND:20250225T200000Z
UID:TALK228871@talks.cam.ac.uk
CONTACT:Cristian Cosentino
DESCRIPTION:This talk will explore various applications of Large Language 
 Models (LLMs) in the medical domain\, focusing on three key topics: struct
 ured information extraction from free-text data\, Alzheimer’s classifica
 tion\, and the integration of Retrieval-Augmented Generation (RAG) with me
 dical information.\n\nThe session will cover how LLMs can be utilized to e
 xtract structured insights from unstructured clinical documents\, improvin
 g the accessibility and usability of medical knowledge. Additionally\, we 
 will discuss their role in Alzheimer’s classification\, evaluating the e
 ffectiveness of fine-tuned LLMs in processing multimodal clinical data for
  early diagnosis. Finally\, we will delve into the integration of RAG to e
 nhance medical information retrieval\, reducing hallucinations and improvi
 ng the reliability of AI-generated responses.\n\nThrough this discussion\,
  we will highlight the challenges and opportunities associated with deploy
 ing LLMs in healthcare\, examining how these models can be optimized for r
 eal-world medical applications. The talk will conclude with insights into 
 future research directions and potential advancements in AI-driven medical
  analysis.\n\n(Cambridge) Harnessing Large Language Models for Medical Dat
 a Processing: Structured Information Extraction\, Disease Classification\,
  and RAG
LOCATION:Lecture Theatre 2\, Computer Laboratory\, William Gates Building
END:VEVENT
END:VCALENDAR