Evaluation of Use of Diagnostic AI for Lung Cancer in Practice
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 15
- 试验地点
- 1
- 主要终点
- Classification accuracy
研究概览
简要总结
This study investigates ways of improving radiologists performance of the classification of CT-scans as cancerous or non-cancerous. Participants interact with an AI to classify CT-scans under three different conditions.
详细描述
The three conditions are as follows: "probabilistic classification", where the radiologist diagnoses scans using an AI cancer likelihood score; "classification plus detection", where the radiologist see detecting lung nodules in addition to the AI's probabilistic classification score before making her own examination of the CT-scan; and "classification with delayed detection", where the radiologist identifies regions of interest independently of the AI and then sees the AI's detected ROIs.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Crossover
- 主要目的
- Diagnostic
- 盲法
- Single (Participant)
入排标准
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •The participant performs radiology screenings professionally
排除标准
- 未提供
研究组 & 干预措施
Classification Plus Detection
Radiologists see a "score" from 1-100 that represents the AI's prediction of whether the CT-scan comes from a patient with cancer or not before beginning their analysis of the scan. They also see ROIs identified by the AI that represent lung nodules.
干预措施: AI-human interaction (Behavioral)
Classification With Delayed Detection
Radiologists see a "score" from 1-100 that represents the AI's prediction of whether the CT-scan comes from a patient with cancer or not before beginning their analysis of the scan. After identifying their own ROIs, the radiologist then can see ROIs identified by the AI that represent lung nodules before making final decisions.
干预措施: AI-human interaction (Behavioral)
Probabilistic Classification
Radiologists see a "score" from 1-100 that represents the AI's prediction of whether the CT-scan comes from a patient with cancer or not before beginning their analysis of the scan.
干预措施: AI-human interaction (Behavioral)
结局指标
主要结局
Classification accuracy
时间窗: up to 4 months after initiation of evaluation of the test set
This compares radiologists' classifications with the ground truth in the tested cases.
次要结局
- detection concordance(up to 4 months after initiation of evaluation of the test set)