일 | 월 | 화 | 수 | 목 | 금 | 토 |
---|---|---|---|---|---|---|
1 | 2 | |||||
3 | 4 | 5 | 6 | 7 | 8 | 9 |
10 | 11 | 12 | 13 | 14 | 15 | 16 |
17 | 18 | 19 | 20 | 21 | 22 | 23 |
24 | 25 | 26 | 27 | 28 | 29 | 30 |
31 |
Tags
- continuity of care
- machine learning in nephrology
- gmai
- mutimodal ai
- ai-powered diagnosis
- legal responsiblity
- on-promise
- essential medical care
- patient's safety
- three lows framework
- retinal imaging for ckd
- tertiary hospital structural reform pilot program
- ccmm
- acute care patient discharge support and community linkage pilot project
- national healthcare insurance
- deep learning in medical imaging
- system reform
- unintended consequences
- Interoperability
- himss
- chronic kidney disease (ckd)
- kidney disease prediction
- early detection of ckd
- digital medicine
- krcore
- ai-based risk stratification
- krcdi
- ai in healthcare
- healthcare policy
- medical reform
Archives
- Today
- Total
목록machine learning in nephrology (1)
Connected Care

1. The Importance of Early CKD DetectionChronic kidney disease (CKD) is a major global health challenge, with most patients diagnosed only after losing more than half of their kidney function. Late detection limits opportunities for early intervention, increasing the likelihood of complications such as kidney failure and cardiovascular disease. To mitigate these risks, early diagnosis and risk s..
Healthcare interoperability
2025. 3. 20. 09:00