浙江大学医学院附属儿童医院2020年-2025年特应性皮炎数据集

高质量、多模态的特应性皮炎临床诊疗数据集，旨在全面描绘该疾病的真实世界图景。在功能形态上，它集成了结构化临床数据与影像数据：结构化数据包含患者主诉、病史、诊断、规范化诊疗方案等完整字段；影像数据则收录了丰富的皮损部位高清图片。这种多模态形态使得数据不仅能进行统计量化分析，更能支持深入的视觉特征挖掘。
该数据集可用于临床研究与智能医疗工具的开发。它可支撑真实世界研究，帮助研究人员分析疾病自然史、评估不同疗法的疗效与安全性，为制定精准的诊疗指南提供循证依据。同时，它可助力医学人工智能的创新发展，作为训练AI模型的核心原料，开发用于辅助诊断、严重程度自动分级和治疗预测的算法工具等。

A high-quality, multimodal clinical diagnosis and treatment dataset for atopic dermatitis is designed to comprehensively depict the real-world landscape of this disease. Structurally, it integrates structured clinical data and imaging data: the structured data covers complete fields such as patients' chief complaints, medical history, diagnosis, and standardized diagnosis and treatment plans; the imaging data includes a rich collection of high-definition images of skin lesion sites. This multimodal format enables the dataset to not only support statistical and quantitative analysis, but also facilitate in-depth visual feature mining.

This dataset can be applied to clinical research and the development of intelligent medical tools. It supports real-world research, helping researchers analyze the natural history of the disease, evaluate the efficacy and safety of different therapies, and provide evidence-based support for formulating precise diagnosis and treatment guidelines. Meanwhile, it can facilitate the innovative development of medical artificial intelligence: as a core training resource for AI models, it can be used to develop algorithmic tools for auxiliary diagnosis, automatic severity grading, treatment prediction and other related scenarios.

搜集汇总

背景与挑战

背景概述

该数据集包含浙江大学医学院附属儿童医院2020-2025年的特应性皮炎结构化临床记录和皮损影像，支持真实世界疗效分析与AI医疗工具开发。多模态特性使其兼具统计分析与视觉特征挖掘价值，可用于诊疗指南优化和智能诊断算法训练。