临床试验中人机交互的定义与分类：一种多维度的人机分类方法

# Defining and Categorising Human-AI Interactions in Clinical Trials: A Multidimensional Human-AI Classification Approach
Source: [https://arxiv.org/abs/2609.38559](https://arxiv.org/abs/2609.38559)
[View PDF](https://arxiv.org/pdf/2609.38559)

> Abstract:This paper examines human\-AI interactions \(HAIIs\) in clinical trials and presents a multidimensional categorisation framework that classifies interactions according to AI tasks, human\-AI relationships, interaction configurations and interacting human groups\. We define HAII, examine existing taxonomies and extend existing categorisation approaches through this novel multidimensional framework\. We purposively sampled 15 clinical trials from a previously reported dataset\. Each trial was independently categorised by two human reviewers and six large language model \(LLM\) classifiers\. The proposed categorisation provides a structured method for the consistent identification, comparison and synthesis of human\-AI interactions across clinical\-trial records\. The framework is intended to support more consistent comparison and synthesis of AI\-related clinical trials and to make explicit the different forms of human involvement associated with AI interventions\. The results demonstrate the potential for LLM\-assisted categorisation while indicating the continuing importance of human judgement where trial records are incomplete or ambiguous\. The principal contribution is a proposed multidimensional framework that brings together AI tasks, human\-AI relationships, interaction configurations and interacting human groups within a single approach designed for clinical\-trial records\. Its significance lies in its potential to support more systematic identification, comparison and synthesis of how humans and AI interact in clinical trials\.

## Submission history

From: Tim Collins \[[view email](https://arxiv.org/show-email/7a23b9cf/2609.38559)\] **\[v1\]**Tue, 29 Sep 2026 21:18:26 UTC \(2,953 KB\)