Enhancing breast cancer screening with AI

Recent research has highlighted that the use of artificial intelligence may be able to diagnose breast cancer earlier, also improving the workload of radiologists.

Using artificial intelligence, breast radiologists in Denmark have improved breast cancer screening performance and reduced the rate of false-positive results.

The discovery comes 16 months after a study from the same hospital found that artificial intelligence could diagnose cancer through chest X-rays as effectively as a certified radiologist.

When used to evaluate likely normal screening results or assist in decision support, artificial intelligence can also substantially reduce the radiologist’s workload.

Dr. Andreas Lauritzen, a researcher at Gentofte Hospital in Denmark and the study’s lead author, stated:

“Population-based mammography screening reduces breast cancer mortality but imposes a significant workload on radiologists who must read a large number of mammograms, most of which do not warrant a patient recall.”

The study

Compared to screening without AI, the AI-assisted screening detected a significantly higher number of breast cancers (0.82% versus 0.70%) and had a lower false-positive rate (1.63% versus 2.39%).

In the AI-screened group, the recall rate, referring to the number of times a patient was asked to return for a follow-up examination, decreased by 20.5%, and the radiologists’ reading workload was reduced by 33.4%.

The positive predictive value of AI-assisted screening was also higher than that of non-AI screening (33.5% versus 22.5%). In the AI group, a larger percentage of detected invasive tumors were 0.4 inches or smaller (44.93% versus 36.60%).

Similarly, a Swedish study conducted at Lund University reported a 20% improvement in accurate breast cancer diagnoses, with the AI’s labor-saving capability being even greater than that observed in Dr. Lauritzen’s study.

An accompanying editorial praised AI’s ability to reduce human workload and suggested that, rather than presenting AI as a potential replacement for radiologists, evidence supports the development of AI programs as work tools and labor-saving devices.

The article draws upon studies published and recommendations from international institutions and/or experts. We do not make claims in the medical-scientific field and report the facts as they are. Sources are indicated at the end of each article.
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