Artificial intelligence solutions designed to help reduce the volume of scans by “weeding out” normal patients and flagging abnormal ones for radiologist review are becoming increasingly popular. Recent evidence presented at radiology conferences points to how these solutions can significantly ...
operational efficiency, and medical research. As we move into 2024, the adoption of AI healthcare tools has accelerated, offering unprecedented benefits and applications.
Radiologist fatigue, especially in high-volume screening environments, leads to decreased accuracy in reading mammograms, increasing the likelihood of missed diagnoses [10,11,12]. Additionally, the variability in imaging equipment and settings further complicates the detection process, as these factors ...