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Role of Instruction-Tuning and Prompt Engineering in Clinical Domain - MedAI 125

Offered By: Stanford University via YouTube

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Oncology Courses Prompt Engineering Courses Instruction-Tuning Courses

Course Description

Overview

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Explore the critical role of instruction-tuning and prompt engineering in advancing Clinical Natural Language Processing (NLP) in this 59-minute talk by Mihir Parmar, a Ph.D. student at Arizona State University and Research Associate at Mayo Clinic. Discover how In-BoXBART leverages instruction-tuning to enhance performance across multiple biomedical tasks and learn about a collaborative Large Language Model (LLM) framework that improves the efficiency and accuracy of systematic reviews in oncology. Gain insights into how these NLP techniques can optimize clinical processes and evidence-based practices. Parmar, an accomplished researcher with publications in top-tier NLP conferences, shares his expertise in pioneering instruction-tuning in the biomedical domain, analyzing instruction impact on model performance, and exploring LLMs' capabilities in question decomposition, program synthesis, and reasoning.

Syllabus

MedAI #125: Role of Instruction-Tuning and Prompt Engineering in Clinical Domain | Mihir Parmar


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Stanford MedAI

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