Artificial Intelligence for Breast Ultrasound: Will It Impact Radiologists’ Accuracy?
Year: 2021
Type: editorial
Abstract: In the setting of breast density notification legislation and the attendant interest in supplemental screening for women with dense breast tissue, screening US has become widely integrated into breast imaging practices (1,2). Screening US detects additional invasive cancers in women with dense breast tissue, with an incremental cancer detection rate averaging 2.1–2.7 per 1000 examinations (3). However, this modality is currently limited by its high recall rate and low positive predictive value of biopsy (1–3). In fact, a recent review article reported that the positive predictive value of biopsies prompted by screening US examinations averages only 9%–11% (3). These limitations, in addition to the wide variability in performance metrics across studies, have fueled interest in the application of artificial intelligence (AI) to screening breast US examinations in order to avoid unnecessary recalls and biopsies (4–10). AI offers the...
Source: Journal of Breast Imaging
DOI: 10.1093/jbi/wbab022
Author: Manisha Bahl
Institution: Massachusetts General Hospital
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3165010860