Artificial Intelligence Augmented Training in Skin Cancer Diagnostics for Skin Cancer Specialists
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 1,500
- 试验地点
- 4
- 主要终点
- Dose/Response
研究概览
简要总结
Background:
The worldwide incidence of skin cancer has been rising for 50 years, in particular the incidence of malignant melanoma has increased approx. 2-7% annually and is the most common cancer amongst Danes aged 15-34. Currently there is a significant amount of misdiagnosis of skin cancer and mole cancer, and most excised skin lesions are benign.
Previous studies have shown that there is no significant increase in doctors diagnostic accuracy during the first 6 years of clinical work.
The resources spend on healthy people could be put to better use, if the Benign-Malignant Ratio could be lowered. This could potentially be done by better educating the doctors during their everyday clinical practice.
Aim:
The aim of this study is to investigate the dose/response effect of an AI augmented training and clinical feedback on the diagnostic accuracy of skin cancer and clinical decisions among doctors from specialized skin cancer centers.
Research question: How much specialized doctors need to train before their diagnostic accuracy and clinical decisions change?
详细描述
Design:
This study is a superiority trial designed as an international multicenter randomized controlled trial of doctors in highly specialized centers that diagnose and/or treat skin- and mole cancer.
Randomization Eligible participants will be randomized into either the intervention or control group, ratio 1:1.
Intervention:
The participants of group A are given access to a digital educational online system developed by the research group, are asked to register all skin lesions seen with a registration app (clinical and dermoscopic photos and clinical data), also developed by the research group, and will be given clinical feedback on every registered skin lesion.
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)
盲法说明
Participating doctors are either given access to an AI augmented digital educational online system or not. During the study period, doctors of both groups are registering skin lesions they encounter in their daily practice using the same hardware and software.
The expert dermatologists that evaluate the registered skin lesions are unaware of the registering doctors allocation.
入排标准
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Doctors are required to work at a specialized skin department (dermatology or plastic surgery or the like).
- •Doctors must be registered authorized health personnel
排除标准
- •Doctors that have previously received access to the DermLoop Learn educational intervention
- •Doctors with less than 2 months left of their affiliation with their current department of employment
研究组 & 干预措施
Group A
This group will receive access to the AI augmented digital online educational system and its two modules (Training Module and Clinical Feedback Module). They will receive continuous clinical feedback on their registered lesions.
干预措施: DermLoop Learn (Other)
Group B
This group is withheld their access to the AI augmented digital online educational system for 2 months.
After the 2 months delay, the subjects in the group are given the same access as the participants in Group A.
结局指标
主要结局
Dose/Response
时间窗: 2 years
Dose/response between hours spent with the education system and change in diagnostic accuracy for the participating doctors
次要结局
- BMR(2 years)
- Multiple-Choice-Questionnaire predictability of diagnostic accuracy(2 months)
- Referrals(2 years)
研究者
Gustav Gede Nervil
Principal Investigator
Herlev Hospital