医学影像数据集|胸部疾病数据集

<p>该数据集包含超过100,000张胸部X光图像，涵盖14种不同胸腔疾病标签，适用于医学图像分类与疾病诊断研究。数据规模大、标签丰富，具有较高的临床代表性，可用于训练和评估深度学习模型。其主要特点在于多类别标注和公开可访问性，广泛应用于联邦学习、医疗AI、影像识别等场景，尤其适合在IoMT（医疗物联网）环境下进行分布式模型训练与验证。</p>

<p>This dataset contains over 100,000 chest X-ray images covering 14 different thoracic disease labels, suitable for medical image classification and disease diagnosis research. With large-scale data, rich annotations, and high clinical representativeness, it can be used to train and evaluate deep learning models. Its main features are multi-class annotations and public accessibility, and it is widely applied in scenarios such as federated learning, medical AI, and image recognition—especially suitable for distributed model training and validation in the IoMT (Internet of Medical Things) environment.</p>