Evidence map›Paper›PMID 39494261›Full record

ArticleAdvanced pharmaceutical bulletin2024

Evaluating the Accuracy of Large Language Model (ChatGPT) in Providing Information on Metastatic Breast Cancer.

Ramakrishna Gummadi, Nagasen Dasari, D Sathis Kumar, Sai Kiran S S Pindiprolu

Abstract readEditorial
In one paragraph

Article in Advanced pharmaceutical bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Applications of Artificial Intelligence (AI) in Breast Cancer Care Delivery and Education: A Scoping Review.International journal of environmental research and public health · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. The Accuracy And Clinical Relevance of Chat GPT-4 in Triple Negative Breast Cancer Research.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ramakrishna GummadiAditya Pharmacy College, Surampalem, Andhra Pradesh, 533 437, India.ORCID https://orcid.org/0000-0001-6576-3576
Nagasen DasariAditya Pharmacy College, Surampalem, Andhra Pradesh, 533 437, India.ORCID https://orcid.org/0000-0002-8305-7277
D Sathis KumarAditya Pharmacy College, Surampalem, Andhra Pradesh, 533 437, India.
Sai Kiran S S PindiproluAditya Pharmacy College, Surampalem, Andhra Pradesh, 533 437, India.ORCID https://orcid.org/0000-0002-5400-4491

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Artificial intelligence (AI), particularly large language models like ChatGPT developed by OpenAI, has demonstrated potential in various domains, including medicine. While ChatGPT has shown the capability to pass rigorous exams like the United States Medical Licensing Examination (USMLE) Step 1, its proficiency in addressing breast cancer-related inquiries-a complex and prevalent disease-remains underexplored. This study aims to assess the accuracy and comprehensiveness of ChatGPT's responses to common breast cancer questions, addressing a critical gap in the literature and evaluating its potential in enhancing patient education and support in breast cancer management. Methods: A curated list of 100 frequently asked breast cancer questions was compiled from Cancer.net, the National Breast Cancer Foundation, and clinical practice. These questions were input into ChatGPT, and the responses were evaluated for accuracy by two primary experts using a four-point scale. Discrepancies in scoring were resolved through additional expert review. Results: Of the 100 responses, 5 were entirely inaccurate, 22 partially accurate, 42 accurate but lacking comprehensiveness, and 31 highly accurate. The majority of the responses were found to be at least partially accurate, demonstrating ChatGPT's potential in providing reliable information on breast cancer. Conclusion: ChatGPT shows promise as a supplementary tool for patient education on breast cancer. While generally accurate, the presence of inaccuracies underscores the need for professional oversight. The study advocates for integrating AI tools like ChatGPT in healthcare settings to support patient-provider interactions and health education, emphasizing the importance of regular updates to reflect the latest research and clinical guidelines.

Indexed as

Artificial intelligenceBreast cancerChatGPTHealthcarePatient education

Identifiers

PMID39494261
PMCPMC11530873

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.