高血压个性化用药推荐数据集

该数据为医院在心内科高血压专病门诊中产生，包含了患者的病史、现病史、合并症（如糖尿病、肾病）、靶器官损害、心电图与心脏彩超结果、既往用药史和住院情况记录。数据形态为结构化病历与监测数据，用于高血压个性化用药推荐模型的开发。业务场景应用于高血压患者的药物调整与长期管理。该数据集可支撑AI模型基于患者特征，结合指南与真实世界疗效数据，推荐初始用药或优化方案（如CCB、ACEI、利尿剂等选择），助力提高血压达标率，减少药物不良反应。

This dataset is collected from the specialized hypertension outpatient clinic of the cardiology department in a hospital. It includes patients' medical history, present illness, comorbidities (e.g., diabetes, nephropathy), target organ damage, electrocardiogram (ECG) and echocardiography results, past medication history, and hospitalization records. The data is in the form of structured medical records and monitoring data, and is utilized for developing personalized hypertension medication recommendation models. Its application scenarios cover medication adjustment and long-term management for hypertension patients. This dataset can support AI models to recommend initial medication or optimized therapeutic regimens (such as selection of CCBs, ACEIs, diuretics, etc.) based on patient characteristics, combined with clinical guidelines and real-world efficacy data, helping to improve blood pressure control rates and reduce adverse drug reactions.

搜集汇总

背景与挑战

背景概述

该数据集来自医院心内科高血压专病门诊，包含患者病史、检查结果及用药记录等结构化数据，用于开发个性化用药推荐模型，帮助优化高血压患者的药物治疗方案。