Related Experiment Video
Updated: Aug 9, 2026
03:14
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Trial Files: Leveraging large language models to summarize practice-changing clinical trials for clinicians
Katarina Zorcic1,2, Emily Bartsch3, Bryant Lim1
1Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada.
Plos One
|August 7, 2026
Summary
Large language models (LLMs) can accurately summarize randomized controlled trials (RCTs), helping clinicians stay current with medical literature. This technology aids medical education by providing concise evidence summaries.
Area of Science:
- Medical Informatics
- Clinical Research
- Artificial Intelligence in Medicine
Background:
- Over 100 randomized controlled trials (RCTs) are published daily, overwhelming clinicians' ability to stay updated.
- Large language models (LLMs) offer a potential solution for summarizing emerging clinical evidence and supporting medical education.
Purpose of the Study:
- To evaluate a novel newsletter, Trial Files, that uses an LLM to summarize RCT abstracts for general internal medicine.
- To assess the accuracy, user satisfaction, and growth strategies of an LLM-powered clinical trial summary tool.
Main Methods:
- Developed 'Trial Files' newsletter using an LLM to summarize RCT abstracts from five high-impact journals via the Medline API.
- Extracted information from RCT abstracts and generated plain-language summaries using OpenAI's LLM API.
- Analyzed LLM summary accuracy against manual review, conducted a subscriber survey, and evaluated marketing strategies for user growth.
Main Results:
- Distributed 50 newsletters with 3 RCTs each to 648 subscribers over 21 months.
- Achieved high accuracy in LLM-generated summaries compared to manual review (e.g., 97.1% for study phase, 92.7% for primary outcome).
- Subscribers rated the newsletter highly (4.7/5) and found it improved their ability to stay updated; conference promotion was the most effective growth strategy.
Conclusions:
- LLMs can generate concise and accurate summaries of RCTs.
- LLM-powered tools like Trial Files can effectively assist general internists in staying current with published clinical trials.
Related Concept Videos
01:16Clinical Trials
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
There are four phases in a clinical trial. A phase one...
01:11Clinical 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...
01:12Statistical Software for Data Analysis and Clinical Trials
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...