填补非洲深肤色人群皮肤病数据空白，推动AI皮肤科公平化
PASSION for Dermatology: Bridging the Diversity Gap with Pigmented Skin Images from Sub-Saharan Africa
- 收集1653名患者4901张非洲儿童皮肤病图像，聚焦常见病种
- 首个针对非洲深肤色人群的公开皮肤病数据集，覆盖儿科常见病
- 提供基准模型与性能分析，助力公平医疗AI研发
非洲皮肤病医生极度短缺，每百万人口不足一人，80%的儿童患有未治疗的皮肤疾病。当前AI皮肤病模型多基于白人皮肤训练，难以泛化至深肤色人群。PASSION项目通过采集撒哈拉以南非洲地区的儿童皮肤病图像，建立首个此类公开数据集，包含1653名患者共4901张图像，涵盖湿疹、真菌感染、疥疮和脓疱病等常见儿科疾病。数据源自远程医疗场景，具有代表性。项目同时提供在该数据集上训练的基准机器学习模型及子群体性能分析。官网：https://passionderm.github.io/
原文摘要 · Abstract (English)
Africa faces a huge shortage of dermatologists, with less than one per million people. This is in stark contrast to the high demand for dermatologic care, with 80% of the paediatric population suffering from largely untreated skin conditions. The integration of AI into healthcare sparks significant hope for treatment accessibility, especially through the development of AI-supported teledermatology. Current AI models are predominantly trained on white-skinned patients and do not generalize well enough to pigmented patients. The PASSION project aims to address this issue by collecting images of skin diseases in Sub-Saharan countries with the aim of open-sourcing this data. This dataset is the first of its kind, consisting of 1,653 patients for a total of 4,901 images. The images are representative of telemedicine settings and encompass the most common paediatric conditions: eczema, fungals, scabies, and impetigo. We also provide a baseline machine learning model trained on the dataset and a detailed performance analysis for the subpopulations represented in the dataset. The project website can be found at https://passionderm.github.io/.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。