A deep learning AI model based on mammographic features can predict cardiovascular risk in women with accuracy comparable to traditional risk scores.
Key Details
- 1Researchers from the George Institute for Global Health developed a deep-learning algorithm using mammogram images and patient age.
- 2The model was trained on 49,196 women with a median follow-up of 8.8 years, 3,392 of whom experienced a major cardiovascular event.
- 3The AI algorithm (DeepSurv) achieved a concordance index of 0.72; traditional risk models range from 0.73 to 0.79.
- 4Combining mammogram radiomics with clinical data increased the concordance index to 0.75.
- 5The model is designed for integration into routine breast cancer screening to provide additional cardiovascular risk information.
Why It Matters
This work demonstrates the potential for mammography-based AI to serve as a dual-purpose screening tool, improving both cancer and cardiovascular disease prevention in women by leveraging existing imaging data. If implemented, it could enhance patient care without adding screening burden or workload.
Source
AuntMinnie
Related News
•Radiology Business
Framework Assesses Real-World Financial Impact of Radiology AI Adoption
A new analysis presents a financial calculator for objectively assessing the return on investment (ROI) of implementing radiology AI solutions.
•Radiology Business
AI Technique Unveils Previously Hidden MS Gray Matter Lesions on MRI
Researchers developed an AI-enhanced method to detect previously invisible gray matter lesions in multiple sclerosis using MRI.
•Radiology Business
Majority of Patients Want Disclosure When AI Used in Imaging
A new survey finds that nearly all patients want to be informed when AI is utilized in medical imaging interpretation.