Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

407
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
407
Clinical Trials: Overview01:11

Clinical Trials: Overview

4.6K
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...
4.6K
Varicose Veins II: Diagnostic Studies and Interprofessional Care01:26

Varicose Veins II: Diagnostic Studies and Interprofessional Care

190
Varicose veins, or varicosities, develop when the valves in the veins, which control blood flow, weaken or damage. It causes blood to pool and the veins to enlarge. Understanding the clinical manifestations, diagnostic approaches, and management options for varicose veins is crucial for effective treatment and relief.Clinical manifestationsClinical manifestations of varicose veins include a heavy, achy feeling or pain after prolonged standing or sitting. This discomfort can often be relieved by...
190
Longitudinal Research02:20

Longitudinal Research

13.1K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
13.1K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

561
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
561

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

CHiLL: Zero-shot Custom Interpretable Feature Extraction from Clinical Notes with Large Language Models.

Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing·2025
Same author

Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature?

Proceedings of machine learning research·2025
Same author

Leveraging Generative AI for Clinical Evidence Synthesis Needs to Ensure Trustworthiness.

ArXiv·2025
Same author

Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models.

Proceedings of machine learning research·2025
Same author

Do Multi-Document Summarization Models <i>Synthesize</i>?

Transactions of the Association for Computational Linguistics·2025
Same author

Artificial intelligence in food and nutrition evidence: The challenges and opportunities.

PNAS nexus·2024
Same journal

Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift.

Proceedings of machine learning research·2026
Same journal

Endo-SemiS: Towards Robust Semi-Supervised Image Segmentation for Endoscopic Video.

Proceedings of machine learning research·2026
Same journal

Perspective: Machine Learning for Health Should Consider Social Drivers of Health.

Proceedings of machine learning research·2026
Same journal

Classifying Phonotrauma Severity from Vocal Fold Images with Soft Ordinal Regression.

Proceedings of machine learning research·2026
Same journal

Does Domain-Specific Retrieval Augmented Generation Help LLMs Answer Consumer Health Questions?

Proceedings of machine learning research·2026
Same journal

Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential.

Proceedings of machine learning research·2026
See all related articles

Related Experiment Video

Updated: Jan 17, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

4.2K

Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs.

Somin Wadhwa1, Jay DeYoung1, Benjamin Nye2

  • 1Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA.

Proceedings of Machine Learning Research
|September 24, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new AI model using Large Language Models (LLMs) to automatically extract key information like interventions, outcomes, and comparators from clinical trial reports, improving evidence-based care.

More Related Videos

Assessment of the Efficacy of An Osteopathic Treatment in Infants with Biomechanical Impairments to Suckling
07:11

Assessment of the Efficacy of An Osteopathic Treatment in Infants with Biomechanical Impairments to Suckling

Published on: February 5, 2019

9.6K
Author Spotlight: Advancements and Challenges in Surgical Treatments for Postamputation Pain
03:26

Author Spotlight: Advancements and Challenges in Surgical Treatments for Postamputation Pain

Published on: March 8, 2024

3.5K

Related Experiment Videos

Last Updated: Jan 17, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

4.2K
Assessment of the Efficacy of An Osteopathic Treatment in Infants with Biomechanical Impairments to Suckling
07:11

Assessment of the Efficacy of An Osteopathic Treatment in Infants with Biomechanical Impairments to Suckling

Published on: February 5, 2019

9.6K
Author Spotlight: Advancements and Challenges in Surgical Treatments for Postamputation Pain
03:26

Author Spotlight: Advancements and Challenges in Surgical Treatments for Postamputation Pain

Published on: March 8, 2024

3.5K

Area of Science:

  • Medical Informatics
  • Natural Language Processing
  • Clinical Trial Analysis

Background:

  • Randomized Controlled Trials (RCTs) are crucial for determining intervention effectiveness and informing evidence-based care.
  • Extracting structured data from unstructured clinical trial reports is a manual, time-consuming process for clinicians.
  • Automating the extraction of key trial elements is essential for efficient evidence synthesis.

Purpose of the Study:

  • To develop and evaluate a text-to-text model using instruction-tuned Large Language Models (LLMs) for automated extraction of Interventions, Outcomes, and Comparators (ICO elements) from clinical abstracts.
  • To infer associated results reported in clinical trial articles.
  • To improve the efficiency and accuracy of evidence extraction from scientific literature.

Main Methods:

  • Utilized instruction-tuned Large Language Models (LLMs) to build a text-to-text model for joint extraction of ICO elements and associated results.
  • Framed evidence extraction as a conditional generation task.
  • Conducted manual (expert) and automated evaluations to assess model performance against previous state-of-the-art (SOTA).

Main Results:

  • The proposed LLM-based model achieved significant improvements, with approximately a 20-point absolute F1 score increase over the previous SOTA.
  • Evaluations demonstrated the effectiveness of framing evidence extraction as a conditional generation task for fine-tuning LLMs.
  • Ablation studies and error analyses were performed to understand model performance drivers and identify areas for future enhancement.

Conclusions:

  • The developed LLM-based approach substantially enhances the automated extraction of structured evidence from clinical trial abstracts.
  • This method offers a more efficient and accurate way to synthesize findings from RCTs, supporting evidence-based medicine.
  • A searchable database of structured findings from RCTs up to mid-2022 has been created and released to facilitate access to synthesized trial results.