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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:20250224T173000Z
DTEND:20250224T203000Z
UID:TALK228853@talks.cam.ac.uk
CONTACT:Pietro Lio
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 classificati
 on\, and the integration of Retrieval-Augmented Generation (RAG) with medi
 cal information.\n\nThe session will cover how LLMs can be utilized to ext
 ract structured insights from unstructured clinical documents\, improving 
 the accessibility and usability of medical knowledge. Additionally\, we wi
 ll discuss their role in Alzheimer’s classification\, evaluating the eff
 ectiveness of fine-tuned LLMs in processing multimodal clinical data for e
 arly diagnosis. Finally\, we will delve into the integration of RAG to enh
 ance medical information retrieval\, reducing hallucinations and improving
  the reliability of AI-generated responses.\n\nThrough this discussion\, w
 e will highlight the challenges and opportunities associated with deployin
 g LLMs in healthcare\, examining how these models can be optimized for rea
 l-world medical applications. The talk will conclude with insights into fu
 ture research directions and potential advancements in AI-driven medical a
 nalysis.\n\n(Cambridge) Harnessing Large Language Models for Medical Data 
 Processing: Structured Information Extraction\, Disease Classification\, a
 nd RAG \n\nGoogle Meet Link: https://meet.google.com/cmn-gjvy-zuy
LOCATION:Lecture Theatre 2\, Computer Laboratory\, William Gates Building
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