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
Real-World Study: Radiology AI Best in Emergency and Inpatient Settings
A commercial AI tool for intracranial aneurysm detection outperformed in inpatient and emergency settings but yielded limited benefits for outpatients in a major health system study.
•Radiology Business
New Rubric Enhances Safety of AI-Generated Radiology Summaries
Researchers developed a five-factor rubric to assess the safety and quality of AI-generated, patient-friendly radiology report summaries.
•Radiology Business
UCLA Review Evaluates Breast AI for Early Cancer Detection
A UCLA-led review analyzes current evidence for AI tools in screening mammography, focusing on their capability to detect interval cancers.