SymbiPredict

The Symptom-Disease Prediction Dataset (SDPD) is a comprehensive collection of structured data linking symptoms to various diseases, meticulously curated to facilitate research and development in predictive healthcare analytics. Inspired by the methodology employed by renowned institutions such as the Centers for Disease Control and Prevention (CDC), this dataset aims to provide a reliable foundation for the development of symptom-based disease prediction models. The dataset encompasses a diverse range of symptoms sourced from reputable medical literature, clinical observations, and expert consensus.症状-疾病预测数据集（Symptom-Disease Prediction Dataset，SDPD）是一套将症状与多种疾病相关联的结构化综合数据集，经精心遴选整理，旨在推动预测型医疗分析领域的研究与开发工作。本数据集借鉴了美国疾病控制与预防中心（Centers for Disease Control and Prevention，CDC）等知名机构的研究方法，旨在为基于症状的疾病预测模型开发提供可靠的基础支撑。该数据集涵盖了从权威医学文献、临床观测及专家共识中获取的多样症状类型。