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

Classification of Illness01:17

Classification of Illness

7.9K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
7.9K
Polygenic Traits01:18

Polygenic Traits

66.5K
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
66.5K
Pedigree Analysis01:35

Pedigree Analysis

85.2K
Overview
85.2K
Genetic Lingo01:11

Genetic Lingo

104.7K
Overview
104.7K
Sex-linked Disorders01:43

Sex-linked Disorders

103.0K
Like autosomes, sex chromosomes contain a variety of genes necessary for normal body function. When a mutation in one of these genes results in biological deficits, the disorder is considered sex-linked.
103.0K
EPS and iPS Cells in Disease Research01:21

EPS and iPS Cells in Disease Research

2.9K
Embryonic and induced pluripotent stem cells are excellent models for disease research because of their ability to self-renew and differentiate into most cell types. Somatic cells from a patient are isolated and reprogrammed into induced pluripotent stem cells or iPSCs. These iPSCs are later differentiated into the desired cell type, which mirrors the diseased cell of the patient. In this way, disease models have been created for investigating diseases such as Down syndrome, type I diabetes,...
2.9K

You might also read

Related Articles

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

Sort by
Same author

Impact of volcanic emissions on the air quality during the 2021 volcanic eruption of Tajogaite, La Palma: Implications for population exposure to volcanic pollutants.

The Science of the total environment·2026
Same author

Navigating the Computational Landscape for Drug Repurposing.

Annual review of pharmacology and toxicology·2026
Same author

Machine learning and deep learning in internal medicine: demystifying concepts.

Revista clinica espanola·2025
Same author

Generative AI: foundational models. Natural Language Processing (NLP) and LARGE Language Models (LLM).

Revista clinica espanola·2025
Same author

Finding patterns in lung cancer protein sequences for drug repurposing.

PloS one·2025
Same author

A lung cancer diagnosis and treatment dataset with geno- and phenotypical characteristics of the patient.

Data in brief·2024
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
See all related articles

Related Experiment Video

Updated: Sep 12, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.7K

Using ChatGPT to Structure Phenotypical Entities from Disease Texts.

Marcel Luis Palacios-Jaén1, Lucía Prieto-Santamaría1,2, Ernestina Menasalvas1,2

  • 1Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Spain.

Studies in Health Technology and Informatics
|August 8, 2025
PubMed
Summary
This summary is machine-generated.

Simple prompts effectively extract phenotypical manifestations from disease texts using ChatGPT. While not surpassing benchmarks, this approach offers a promising avenue for biomedical text mining of phenotypic data.

Keywords:
ChatGPTLarge Language Models (LLMs)Phenotypical Entities

More Related Videos

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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

Published on: December 6, 2024

682
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

8.8K

Related Experiment Videos

Last Updated: Sep 12, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.7K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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

Published on: December 6, 2024

682
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

8.8K

Area of Science:

  • Biomedical Informatics
  • Natural Language Processing
  • Artificial Intelligence

Background:

  • Accurate extraction of phenotypical entities from unstructured biomedical texts remains a challenge.
  • Advancements in AI, like large language models, offer new possibilities for text mining.

Purpose of the Study:

  • To explore the effectiveness of ChatGPT 3.5 Turbo with prompt engineering for extracting phenotypical data from disease texts.
  • To compare the performance of different prompt strategies against established tools like UMLS MetaMap.

Main Methods:

  • One hundred Wikipedia disease texts were processed using ChatGPT 3.5 Turbo.
  • Various prompt engineering techniques were tested, including simple keyword focus, entity dictionaries, explanation steps, and prompt chaining.
  • Results were evaluated using precision, recall, and F1 scores, benchmarked against UMLS MetaMap.

Main Results:

  • Simpler prompts focused on "Phenotypical Manifestations" achieved the highest F1 score of 0.60.
  • Complex prompts and advanced techniques like one-shot examples or prompt chaining yielded lower performance.
  • Including the keyword "manifestations" improved recall.

Conclusions:

  • Straightforward prompting strategies are more effective for extracting phenotypical data entities using ChatGPT.
  • While promising, current ChatGPT performance for this task is below the UMLS MetaMap benchmark.
  • Further refinement of prompt engineering is needed to enhance accuracy in biomedical text mining.