Evidence map›Paper›PMID 37516680›Full record

ArticleAnnals of biomedical engineering2024

ChatGPT and Clinical Decision Support: Scope, Application, and Limitations.

Jannatul Ferdush, Mahbuba Begum, Sakib Tanvir Hossain

Abstract readLetter
PubMed Publisher
In one paragraph

Article in Annals of biomedical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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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

3 authors.

Jannatul Ferdush *Department of Computer Science and Engineering, Jashore University of Science and Technology, Jashore, 7408, Bangladesh. jannatulferdush@just.edu.bd.
Mahbuba Begum *Department of Computer Science and Engineering, Mawlana Bhasani Science and Technology, Tangail, 1902, Bangladesh.
Sakib Tanvir Hossain *Department of Mechanical Engineering, Khulna University of Engineering and Technology, Khulna, 9203, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines ChatGPT's role in clinical decision support, by analyzing its scope, application, and limitations. By analyzing patient data and providing evidence-based recommendations, ChatGPT, an AI language model, can help healthcare professionals make well-informed decisions. This study examines ChatGPT's use in clinical decision support, including diagnosis and treatment planning. However, it acknowledges limitations like biases, lack of contextual understanding, and human oversight and also proposes a framework for the future clinical decision support system. Understanding these factors will allow healthcare professionals to utilize ChatGPT effectively and make accurate clinical decisions. Further research is needed to understand the implications of using ChatGPT in healthcare settings and to develop safeguards for responsible use.

Indexed as

Artificial IntelligenceDecision Support Systems, ClinicalHealth PersonnelHumansBiasnessCDSChatGPTEthics

Identifiers

What OpenQuestion holds

Textmetadata
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.