Trends in AI and Human-AI Interaction in Clinical Trials -- A Hybrid Human-AI Exploration
Quick Take
This study analyzes AI trends in clinical trials using a hybrid human-AI approach, revealing a significant rise in AI-related trials, particularly in the US and China. The findings highlight the need for clearer trial reporting and definitions of human-AI interactions to enhance screening processes.
Key Points
- AI-related clinical trials have significantly increased over time, especially in the US and China.
- Notable growth in terms like machine learning, deep learning, and large language models was observed.
- Hybrid screening using GPT-5.5 and human review showed good agreement in identifying non-AI studies.
- Lower agreement was found in classifying ambiguous human-AI interactions.
- Improved trial reporting and interaction definitions are essential for effective screening.
Article Content
From source RSS / original summaryarXiv:2605. 29096v1 Announce Type: new Abstract: This paper examines records retrieved from the ClinicalTrials. gov registry to characterize temporal trends in AI terminology and the geographical distribution of AI trials. The work also reports on an exploratory hybrid human-AI approach to analyzing human-AI interaction trends in registered clinical trials. The hybrid workflow comprised a frontier generative AI model (GPT-5. 5) and human review to screen and categorize records returned by an AI-focused search.
The findings indicate a marked increase in AI-related trials over time, with recent growth in references to machine learning, deep learning, chatbots, GPTs, and large language models. Geographically, China and the United States accounted for the largest numbers of AI-related trials, with notable recent increases in several other countries including Italy, France, Spain, the UK and Turkey (T\"urkiye).
In a random sample of 100 records, human and AI classifiers showed good agreement in identifying studies not substantively using AI, but lower agreement in classifying human-AI interaction, particularly where health professional interaction was ambiguous or insufficiently described. Overall, the results suggest that hybrid human-AI screening of clinical trial records is potentially viable, but clearer trial reporting and more precise interaction definitions will benefit the process.
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