| 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 |
Tags
- machine learning in nephrology
- patient's safety
- early detection of ckd
- tertiary hospital structural reform pilot program
- gmai
- krcore
- chronic kidney disease (ckd)
- three lows framework
- acute care patient discharge support and community linkage pilot project
- healthcare policy
- essential medical care
- deep learning in medical imaging
- retinal imaging for ckd
- ccmm
- ai-based risk stratification
- system reform
- kidney disease prediction
- national healthcare insurance
- medical reform
- unintended consequences
- himss
- continuity of care
- legal responsiblity
- digital medicine
- ai-powered diagnosis
- Interoperability
- ai in healthcare
- krcdi
- on-promise
- mutimodal ai
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