JPRN-UMIN000044665尚未招募未知
Creating a model to support clinical decision by predicting intraoperative vital signs using artificial Intelligence - Creating a model to support clinical decision by predicting intraoperative vital signs using artificial Intelligence
适应症
试验速览
- 阶段
- 未知
- 状态
- 尚未招募
- 入组人数
- 40,000
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
- 1days-old 至 150years-old(—)
- 性别
- All
入选标准
- 未提供
排除标准
- •If the patient or the patient's guardian refuses to participate in the research. Patients who are judged inappropriate by the principal investigator
研究者
相似试验
已完成
不适用
Optimizing management of musculoskeletal pain disorders in primary physiotherapy careImproved treatment outcome for patients with common musculoskeletal disorders such as neck, shoulder, low back, hip, knee and multisite painMusculoskeletal DiseasesISRCTN17927832orwegian University of Science and Technology724
已完成
不适用
Development and validation of clinical decision rules for cervical CT and MRI in trauma patientscervical spine injury, cervical spinal cord injury without bony injuryJPRN-UMIN000011283ational Center for Global Health and Medicine Hospital2,000
已完成
不适用
nderstanding and predicting recovery in patients undergoing total knee replacementTotal Knee Arthroplasty (TKA)knee replacementMusculoskeletal - OsteoarthritisMusculoskeletal - Other muscular and skeletal disordersACTRN12619001000190Centre for Rehab Innovations, University of Newcastle1,148
尚未招募
不适用
Development of a prediction models for clinical outcomes of patients with peritoneal dialysis based on home-based monitoring : Using deep learning methodsDiseases of The genitoruinary systemKCT0005608Yonsei University Health System, Severance Hospital100
尚未招募
Unknown
Development of a prognostic model to predict core outcome in older adults with hip fracturesHip fractureJPRN-UMIN000051376Hidaka Rehabilitation Hospital400
