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

Three-Compartment Open Model01:06

Three-Compartment Open Model

1.2K
The three-compartment open model is a pharmacokinetic model used to describe the distribution and elimination of drugs following extravascular administration. It comprises a central compartment representing the plasma and two peripheral compartments. The highly perfused peripheral compartment represents organs and tissues with a rich blood supply, such as the liver, kidneys, and lungs. The scarcely perfused peripheral compartment represents tissues with lower blood supply, such as adipose...
1.2K

You might also read

Related Articles

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

Sort by
Same author

Phototype-related Trichoscopic differences in lichen Planopilaris and frontal Fibrosing alopecia.

Journal of the European Academy of Dermatology and Venereology : JEADV·2026
Same author

Fluid dynamics-informed CCTA-derived geometric parameters in right coronary artery anomalies predict abnormal invasive Adenosine-FFR and Dobutamine-FFR.

Computers in biology and medicine·2026
Same author

Real-World Effectiveness and Safety of Ritlecitinib in Adolescents with Severe Alopecia Areata: A 36-Week Single-Center Study.

Journal of the American Academy of Dermatology·2026
Same author

Influence of radiofrequency electromagnetic radiation on spermatogenesis and sperm function in rodent models: A systematic review.

Reproductive toxicology (Elmsford, N.Y.)·2026
Same author

The worldwide burden of skin diseases: Lessons from the Global Burden of Disease data.

Journal of the European Academy of Dermatology and Venereology : JEADV·2026
Same author

Occipital short anagen syndrome: Epidemiological, clinical and trichoscopy features of a case series.

Journal of the European Academy of Dermatology and Venereology : JEADV·2026

Related Experiment Video

Updated: May 1, 2026

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

3.2K

Publicly Available Large Language Models for Trichoscopy: A Head-to-Head Comparison with Dermatologists.

Basil Signer1, Ali Mokhtari2, Simone Cazzaniga1

  • 1Department of Dermatology, Inselspital, Bern University Hospital, 3010 Bern, Switzerland.

Diagnostics (Basel, Switzerland)
|January 10, 2026
PubMed
Summary

Large language models (LLMs) show limited diagnostic accuracy in trichoscopy, significantly underperforming human experts. Further development is needed for AI to assist reliably in hair and scalp disorder diagnoses.

Keywords:
alopeciaartificial intelligencecomparative studydermatologistsdiagnostic accuracylarge language modelsprospective studytrichoscopy

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

1.0K
Dermoscopy Aids in the Diagnosis of Discoid Lupus Erythematosus
05:39

Dermoscopy Aids in the Diagnosis of Discoid Lupus Erythematosus

Published on: May 16, 2025

541

Related Experiment Videos

Last Updated: May 1, 2026

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

3.2K
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

1.0K
Dermoscopy Aids in the Diagnosis of Discoid Lupus Erythematosus
05:39

Dermoscopy Aids in the Diagnosis of Discoid Lupus Erythematosus

Published on: May 16, 2025

541

Area of Science:

  • Dermatology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Trichoscopy is crucial for diagnosing hair and scalp disorders, demanding significant expertise.
  • The diagnostic utility of publicly available large language models (LLMs) in trichology remains unexplored.
  • This study assesses LLMs' accuracy in interpreting trichoscopic images against human dermatologists.

Purpose of the Study:

  • To evaluate the diagnostic accuracy of four LLMs in trichoscopic image interpretation.
  • To compare LLM performance against dermatology residents, board-certified dermatologists, and trichology experts.
  • To determine the potential of AI in assisting trichological diagnoses.

Main Methods:

  • A prospective comparative study using a preprocessed set of structurally transformed trichoscopic images.
  • Fifteen dermatologists (residents, board-certified, experts) provided suspected and differential diagnoses.
  • Four LLMs (ChatGPT-4o, Claude Sonnet 4, Gemini 2.5 Flash, Grok-3) evaluated images under identical conditions.

Main Results:

  • Human dermatologists achieved an overall diagnostic accuracy of 58.1% for suspected diagnoses and 68.3% for suspected + differential diagnoses.
  • AI models achieved lower accuracy: 18.2% for suspected diagnoses and 44.4% for suspected + differential diagnoses.
  • Gemini 2.5 Flash showed the highest AI accuracy (62.5% for suspected + differential diagnoses), yet all AI models significantly underperformed human experts (p < 0.001).

Conclusions:

  • Publicly available LLMs currently underperform human experts in trichoscopic diagnosis, particularly for single correct diagnoses.
  • AI models demonstrate moderate to good agreement among themselves but show only slight to fair agreement with dermatologists.
  • Specialized training and further development are essential for LLMs to be reliable tools in routine trichological care.