In a new study on ultrasound screening for breast cancer, a “hybrid” of radiologists and a deep learning algorithm has yielded a lower biopsy rate and higher accuracy than that achieved by either the human experts or the artificial intelligence (AI) algorithm alone.
The findings, which at the time of this writing await peer review, echo the results of a 2019 study of mammography exams and strengthen the case that machine learning has the potential to help radiologists more accurately diagnose the most common malignancy among women. But before collaborations between radiologists and AI can benefit patients, the technology has to become more transparent.
To learn more about the study and how researchers are trying to bring algorithms and people together, open the visual story below.
Artificial Intelligence System Reduces False-Positive Findings in the Interpretation of Breast Ultrasound Exams.
medRxiv. April 30, 2021. doi: 10.1101/2021.04.28.21256203
September 24, 2021
Research featured in this post has been peer reviewed and published.
Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams.
Nat Commun. 2021 Sep 24;12(1):5645. doi: 10.1038/s41467-021-26023-2