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Improving Translational Accuracy

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Clinical Trials: Overview

Clinical Trials: Overview

Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...

Clinical Trials

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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

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Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts.

Dave Van Veen^1,2, Cara Van Uden^2,3, Louis Blankemeier^1,2

¹Department of Electrical Engineering, Stanford University, Stanford, CA, USA.

Research Square

|November 14, 2023

Summary

Large language models (LLMs) now outperform human experts in summarizing clinical text across multiple tasks. This advancement in natural language processing (NLP) can reduce clinician documentation burden, improving patient care.

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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

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Area of Science:

Artificial Intelligence
Clinical Informatics
Natural Language Processing

Background:

Clinicians face significant time burdens summarizing electronic health records (EHR).
Large language models (LLMs) show promise for NLP but require validation in diverse clinical summarization tasks.

Conclusions:

This study provides the first evidence of LLMs outperforming human experts in multi-task clinical text summarization.
Integrating adapted LLMs into clinical workflows can potentially alleviate documentation burdens.
LLM adoption may enable clinicians to dedicate more time to patient care and the human aspects of medicine.