Design and Development of AI-based solution to predict the early stage of diabetic foot complications empowering diabetic foot care
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Development of machine learning algorithm for early detection of diabetic foot complication.
研究概览
简要总结
Diabetes mellitus (DM) is a chronic, continually growing metabolic disease that can be brought on by an inability to produce insulin or by an intolerance to the hormone. The number of estimated sufferers in India is 77 million. Diabetic foot complications (DFC) include neuropathies, calluses, poor circulation, and foot ulcers caused by ischemia, neuropathy, and microvascular and macrovascular damage. DFC is a common but serious complication of diabetes mellitus (DM). These issues contribute to morbidity and mortality by facilitating the development of infections, ulcers, and gangrene. Diabetic foot lesions not only result in pain and morbidity but also have major financial consequences. Early detection of DFC and foot care practices as a preventive measure have shown promising results in prevention of DFC. Hence the aim of the study is to develop and design AI based solution for early diagnosis of diabetic foot complications and to empower foot care practices.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 30.00 Year(s) 至 70.00 Year(s)(—)
- 性别
- All
入选标准
- •People with type 2 diabetes mellitus People with type 2 diabetes mellitus and diagnosed with diabetic foot complications Normal Healthy individuals Both gender (Male/Female) 30-70 years.
排除标准
- •People with venous foot ulcerations People with bilateral Syme’s Amputation and above.
结局指标
主要结局
Development of machine learning algorithm for early detection of diabetic foot complication.
时间窗: Baseline one time assessment
次要结局
- App Usability questionnaire(Post 3 weeks of application delivery to the user)
研究者
Mariya Jiandani
Physiotherapy School and Centre Seth G S Medical College and KEMH
