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临床试验/NCT06748170
NCT06748170已完成不适用

Al to Improve the Diagnosis of Rare Rheumatic Diseases

Philipps University Marburg1 个研究点 分布在 1 个国家目标入组 68 人开始时间: 2025年1月7日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
已完成
发起方
入组人数
68
试验地点
1
主要终点
Diagnostic accuracy of top diagnosis

研究概览

简要总结

This trial aims to assess the impact of providing medical students with access to ChatGPT, a state-of-the-art large language model, in comparison to conventional diagnostic decision support tools, on their diagnostic accuracy for rare rheumatic diseases.

详细描述

Advanced artificial intelligence (AI) technologies, particularly large language models such as OpenAI's ChatGPT, hold significant potential for enhancing medical decision-making. While ChatGPT was not specifically designed for medical applications, it has shown utility in various healthcare scenarios, including answering patient inquiries, drafting medical documentation, and aiding consultations. Despite these advancements, its role in supporting diagnostic reasoning-especially among less experienced medical students-and for complex rare diseases remains underexplored.

Diagnostic reasoning is a multifaceted process that combines pattern recognition, knowledge synthesis, and probabilistic thinking. Tools like ChatGPT could potentially alleviate cognitive burden, enhance diagnostic accuracy, and ultimately accelerate the diagnosis for rare diseases. However, ChatGPT is not tailored for diagnostic reasoning and lacks comprehensive validation in this domain. Additionally, it is susceptible to generating misinformation or plausible-sounding but inaccurate responses, which may hinder rather than support clinical decision-making. Therefore, understanding how medical students utilize such AI tools is essential before they are integrated into educational or clinical workflows. This study will also assess a standardized prompt to facilitate ChatGPT usage and will give students direct access to enable a realistic scenario.

This study will investigate the impact of ChatGPT on the diagnostic accuracy of medical students when tackling cases of rare rheumatic diseases. Participants will be randomized into two groups: one with access to ChatGPT and one using conventional diagnostic tools. Each participant will analyze diagnostic cases by providing up to 5 differential diagnoses and and rating the diagnostic confidence. Independent reviewers, blinded to group allocation, will evaluate the accuracy and quality of their responses. This study hence aims to provide insights into the potential benefits and limitations of integrating AI tools like ChatGPT.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Diagnostic
盲法
Single (Outcomes Assessor)

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者
是

入选标准

  • •Medical students having started with clinical subjects (Internal medicine)

排除标准

  • •Not being a medical student

研究组 & 干预措施

Intervention group

Active Comparator

Group will be given access to ChatGPT and standardized initial prompt

干预措施: ChatGPT (Other)

Control group

No Intervention

Group will not be given access to any LLMs including ChatGPT but will be motivated to use other resources (such as online search enginges, Pubmed)

结局指标

主要结局

Diagnostic accuracy of top diagnosis

时间窗: during evaluation

Participants in each group will make at least one disease suggestion (top diagnosis) and up to a total of a maximum of 5 suggestions. Percentage of exact matches of the top suggestion with the actual diagnosis will be analyzed

次要结局

  • Diagnostic confidence(during evaluation)
  • Diagnostic accuracy of top 5 suggestions(during evaluation)
  • Diagnostic reasoning(during evaluation)
  • Time spent for diagnosis(during evaluation)

研究者

发起方
Philipps University Marburg
申办方类型
Other
责任方
Sponsor

研究点 (1)

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