Summary of Artificial Intelligence-based Opportunistic Coronary Calcium Screening in the Veterans Affairs National Healthcare System, by Raffi Hagopian et al.
Artificial Intelligence-Based Opportunistic Coronary Calcium Screening in the Veterans Affairs National Healthcare System
by Raffi Hagopian, Timothy Strebel, Simon Bernatz, Gregory A Myers, Erik Offerman, Eric Zuniga, Cy Y Kim, Angie T Ng, James A Iwaz, Sunny P Singh, Evan P Carey, Michael J Kim, R Spencer Schaefer, Jeannie Yu, Amilcare Gentili, Hugo JWL Aerts
First submitted to arxiv on: 16 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A deep learning algorithm called AI-CAC was developed to automatically quantify coronary artery calcium (CAC) from non-contrast, non-gated CT scans. This algorithm outperformed the clinical standard ECG-gated CAC scoring in differentiating between zero vs. non-zero and less than 100 vs. 100 or greater Agatston scores. The AI-CAC algorithm was also predictive of all-cause mortality and composite first-time stroke, MI, or death. Additionally, it was able to identify patients who would benefit from lipid-lowering therapy. This study demonstrates the potential of AI-CAC for cardiovascular risk assessment and management. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI-CAC is a new way to measure coronary artery calcium using CT scans. It’s like a super smart computer program that can look at your scan and tell how much calcium you have in your arteries. This helps doctors predict if you might get heart problems or even die from them. The AI-CAC program was tested on many people and worked really well. It even helped identify who needs to take medicine to lower their cholesterol levels. |
Keywords
» Artificial intelligence » Deep learning
