NCT07292116尚未招募不适用
Prediction of Disease Progression Using Machine Learning Based on Clinical Data in People With Multiple Sclerosis
Hüseyin Bektaş0 个研究点目标入组 53 人开始时间: 2025年12月15日最近更新:
适应症
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 53
- 主要终点
- Fragility level
研究概览
简要总结
Demographic and clinical data will be obtained from people with MS. Based on this data, the progression of the disease will be predicted with artificial intelligence.
详细描述
Demographic and clinical data will be obtained from people with MS. Demographic data; age, gender, disease type, disease duration. Clinical data; Frailty, Physical Activity Level, Walking, Balance, Fatigue, Quality of Life. Based on these data, disease progression will be predicted with artificial intelligence and motor learning.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Having been diagnosed with MS
排除标准
- •be literate
结局指标
主要结局
Fragility level
时间窗: 3 month
The level of frailty will be measured by the Frailty Index.
次要结局
未报告次要终点
研究者
Hüseyin Bektaş
uzman
Pamukkale University
相似试验
招募中
不适用
PrograMSMultiple SclerosisNL-OMON21916VU University Medical Center260
招募中
不适用
ongitudinal prediction of progression in MS: The PrograMS CohortMSDisseminated sclerosis10012303NL-OMON51918Vrije Universiteit Medisch Centrum300
已完成
不适用
Artificial Intelligence in Predicting Progression in Multiple Sclerosis StudyMultiple Sclerosis LesionMultiple Sclerosis Brain LesionMultiple SclerosisNCT05426980University of Ljubljana654
招募中
不适用
Research on a Machine Learning-Based Predictive Model for Difficult Intubation Using Specific Vocal CharacteristicsDifficult Airway IntubationNCT07278232Shanghai Jiao Tong University Affiliated Sixth People's Hospital300
招募中
不适用
Multiple Sclerosis Prediction and Monitoring of Progression StudyProgressive Multiple SclerosisNCT05685784University Hospital, Ghent70