CTRI/2020/10/028256尚未招募未知
To test the feasibility of a novel machine-learned triage software, Datos inconjunction with pulse oximeter and temperature device for remote screening, monitoring, and triage of oncology patients infected with COVID-19.
Tata Memorial Hospital Research Administrative Council0 个研究点目标入组 0 人开始时间: 待定最近更新:
试验速览
- 阶段
- 未知
- 状态
- 尚未招募
- 发起方
研究概览
简要总结
暂无简介。
研究设计
- 研究类型
- Interventional
入排标准
入选标准
- •1. Male or Female adults age greater than or equal to 18 years old.
- •2. All Patients must have an oncologic diagnosis.
- •3. Patients must be positive for COVID-19 and require outpatient monitoring.
- •4. ECOG greater than or equal to 2.
- •5. Able to sign informed consent and to comply with protocol.
- •6. Patients must be comfortable with using the pulse oximeter and thermometer device as well as be able to follow basic instructions for the device in the opinion of the study team.
排除标准
- •1. Clinical illness requiring hospitalization.
- •2. Unable to consent, use and follow the study device instructions for the entire study period.
- •3. Substance and/or alcohol abuse
研究者
相似试验
已完成
不适用
Deep learning prognostic model for pancreatic cancerNeoplasmsKCT0007154Asan Medical Center2,584
尚未招募
Unknown
Artificial Intelligence Approach to Early Detection of Breast and Cervical Cancers in Indian Patients.CTRI/2024/04/065171AIIMS New Delhi
已完成
不适用
Development and exploration of an AI model to classify healthy subject and suspected schizophrenia patient based on free conversations with medical staffSchizophreniaJPRN-jRCT1030210514Yuichiro Tsutsumi150
招募中
不适用
Development and exploration of an AI model to classify schizophrenia with signs of relapse and schizophrenia with no signs of relapse based on free conversations with medical staffSchizophreniaJPRN-jRCT1030220320Toyoshiba Hiroyoshi100
尚未招募
不适用
Predicting Difficult Airway Management Through Machine Learning of Patient PhotographKCT0004193Hallym University2,000