JPRN-UMIN000042073招募中未知
Machine learning prediction of Heart failure and Arrythmia using the mobile self-monitoring ECG devices - Machine learning prediction of Heart failure and Arrythmia using the mobile self-monitoring ECG devices
niversity of Tokyo0 个研究点目标入组 500 人开始时间: 2020年10月11日最近更新:
试验速览
- 阶段
- 未知
- 状态
- 招募中
- 发起方
- 入组人数
- 500
研究概览
简要总结
暂无简介。
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 20years-old 至 ot applicable（—）
- 性别
- All
入选标准
- 未提供
排除标准
- •Individual under 20 years
研究者
相似试验
招募中
不适用
Software to evaluate clinical, epidemiological data and chest computed tomography to predict which patients with COVID-19 will develop a severe form of the disease.RBR-7dsxsvDiagnósticos da América Sociedade Anônima (DASA)
已完成
不适用
Prediction of development and severity of heart failure by machine learning of Holter ECG testHeart failureJPRN-UMIN000046696Fujita Health University500
尚未招募
Unknown
Deep Learning-Based Prediction of Cardiovascular Outcomes using Optical Coherence Tomography in Patients with Acute Coronary Syndromeacute coronary syndromeJPRN-UMIN000049237Kobe University, department of cardiology360
已完成
不适用
Development of a Predictive Algorithm for the Risk of Rehospitalization of Patients With Heart FailureHeart FailureNCT03905226Fondation Hôpital Saint-Joseph1,486
招募中
不适用
Predictors of outcome in heart failure with preserved ejection fractioI50.19I27.28DRKS00004573Medizinische Universität Wien, Allgemeines Krankenhaus der Stadt Wien, Universitätsklinik II für Innere Medizin , Abteilung für Kardiologie350