Women’s imaging encompasses many radiology procedures related to women and the diseases that are most prevalent to women such as breast cancer or gynecological issues. Mammogram, breast ultrasound, breast MRI and breast biopsy are the most commonly used procedures.
New findings support the routine use of deep learning-based risk assessments, as this method can decrease subjectivity, reduce unnecessary imaging and improve diagnostic accuracy.
The 4D system harnesses X-ray diffraction to measure molecular-level signatures of disease; these tissue “fingerprints” could help providers diagnose breast cancer in its earliest stages.
This approach can be replicated by radiologist-led teams elsewhere, providing a "high-value, scalable opportunity" to reduce cancer screening disparities.
Automatically scheduling patients for breast imaging also created a heavier administrative burden, researchers detailed Monday in JAMA Internal Medicine.
“It’s vital that imaging centers have a process in place to provide ongoing monitoring of AI once it becomes part of clinical practice,” one expert noted.