由于实验室检测的可靠性较低，皮肤病更适合用AI模型进行诊断。图像与文本结合的AI皮肤科诊断模型有限；其中很少有针对亚洲人群的，也很少涵盖最常见的疾病类型。利用来自亚洲的包含超过 200,000 张图像和 220,000 份医疗记录的数据集，我们探索了一种基于深度学习的双通道图像系统，并提取了文本皮肤病诊断模型DIET-AI可诊断31种皮肤病，涵盖大部分常见皮肤病。 2021年9月1日至12月1日，我们前瞻性收集了中国7个省份15家医院的6,043例病例的图像和医疗记录。然后将DIET-AI的表现与临床数据集中六位不同资历的医生的表现进行比较。DIET-AI在31种疾病中的平均表现不低于所有不同资历的医生的平均表现。通过比较曲线下面积、敏感性和特异性，我们证明 DIET-AI 模型在临床场景中是有效的。此外，病历不同程度地影响着DIET-AI和医生的表现。这是针对中国人群的最大的皮肤病学数据集。我们首次在包含图像和病历的非癌性皮炎数据集上建立了双通道图像分类模型，并取得了与高级医生对常见皮肤病的诊断性能相当的性能。为后续探索DIET-AI在临床应用的可行性和性能评估提供参考。版权所有©2023 Li,Zhang,Wei,Qian,Tang,Hu,Huang,Xia,Zhang,Cheng,Yu,Zhang,Dan,Liu,叶、何、蒋、刘、范、宋、周、王、张、吕。

Due to the lower reliability of laboratory tests, skin diseases are more suitable for diagnosis with AI models. There are limited AI dermatology diagnostic models combining images and text; few of these are for Asian populations, and few cover the most common types of diseases.Leveraging a dataset sourced from Asia comprising over 200,000 images and 220,000 medical records, we explored a deep learning-based system for Dual-channel images and extracted text for the diagnosis of skin diseases model DIET-AI to diagnose 31 skin diseases, which covers the majority of common skin diseases. From 1 September to 1 December 2021, we prospectively collected images from 6,043 cases and medical records from 15 hospitals in seven provinces in China. Then the performance of DIET-AI was compared with that of six doctors of different seniorities in the clinical dataset.The average performance of DIET-AI in 31 diseases was not less than that of all the doctors of different seniorities. By comparing the area under the curve, sensitivity, and specificity, we demonstrate that the DIET-AI model is effective in clinical scenarios. In addition, medical records affect the performance of DIET-AI and physicians to varying degrees.This is the largest dermatological dataset for the Chinese demographic. For the first time, we built a Dual-channel image classification model on a non-cancer dermatitis dataset with both images and medical records and achieved comparable diagnostic performance to senior doctors about common skin diseases. It provides references for exploring the feasibility and performance evaluation of DIET-AI in clinical use afterward.Copyright © 2023 Li, Zhang, Wei, Qian, Tang, Hu, Huang, Xia, Zhang, Cheng, Yu, Zhang, Dan, Liu, Ye, He, Jiang, Liu, Fan, Song, Zhou, Wang, Zhang and Lv.