AI-Powered Mammography for Faster, More Accurate Breast Cancer Detection
Reduce Recall Rate
The “comma“ intelligent assistant technology helps reduce recall rates by up to 20%, ensuring only clinically significant findings trigger additional scans.
A clinical study demonstrated a reduction in average recall rates from 35–40% to 20–25% through the integration of AI-assisted mammography. This significant decline highlights the technology’s ability to improve diagnostic accuracy by reducing false positives—cases where patients are unnecessarily called back for additional imaging or biopsies due to ambiguous findings.
Enhanced Accuracy and Sensitivity
The “comma“ intelligent assistant technology improves the precision and sensitivity of mammography interpretation, playing a pivotal role in early breast cancer detection. Deep learning algorithms can identify subtle patterns in medical images, reducing human error. Studies demonstrate that combining radiologists’ expertise with AI increases the detection rate of suspicious lesions while decreasing false negatives.
Assistant as radiologist’s second eye
The “comma“ intelligent assistant technology has been trained on over 400,000 mammography images along with thousands of positive biopsied tests, which is still learning. AI as a “second eye“ is completely possible to degrade the number of missed cancerous tissues by “20.9%”.
An assistant as accurate as a radiologist
The trained AI technology has a high sensitivity of 88.3%. This accuracy can enhance the diagnosis metric by 19.8% becoming identical to an expert.
However, we believe this accuracy could get to a higher level which our goal is to reach it.
Accurate diagnosis acceleration
According to the results of scientific tests, using “comma“ as an intelligent assistant can effectively reduce the time of accurate analysis of mammography images by “45%“.
Mammograms analyzed by GITAI
