This retrospective study explored whether artificial intelligence (AI) had the ability to detect type 2 diabetes mellitus through the evaluation of the pectoral muscle on digital breast tomosynthesis (DBT). Through an analysis of over 11,500 DBT images from 300 female patients, the authors found that applying deep learning for the detection of diabetes mellitus in women found an accuracy of 92%. Key points: AI may have an opportunistic use as a screening exam for diabetes during digital breast tomosynthesis. This technique allows for early and non-invasive detection of diabetes mellitus by AI. AI may have broad applications in detecting pathological changes within muscle tissue. Article: Can artificial intelligence detect type 2 diabetes in women by evaluating the pectoral muscle on tomosynthesis: diagnostic study Authors: Meltem M. Yashar, Ilayda Begum Izci, Fatma Zeynep Gungoren, Abdulkadir A. Eren, Ali A. Mert & Irmak I. Durur-Subasi
Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations
Deep‑learning reconstruction (DLR) shifts CT image formation from a hardware‑limited process to a data‑driven one. In our real‑world cohort of >10,000 body scans, we observed a
28. April 2025
