Diagnostic screening programs help catch cancer, abnormalities or other diseases before they reach an advanced stage, saving lives and healthcare costs. Screening programs include, lung, breast, prostate, and cervical cancer, among many others.
New findings support the routine use of deep learning-based risk assessments, as this method can decrease subjectivity, reduce unnecessary imaging and improve diagnostic accuracy.
The COlorectal Cancer detection with AI, or COCA, model is a cost-effective, scalable solution that turns routine CT scans into opportunistic exams that can be used to proactively identify CRC.
Two respected radiology organizations have issued a stark warning on the new recommendations, stating that they risk confusing patients and “may contribute to thousands of additional breast cancer deaths each year.”
The document provides an in-depth look at the close relationship between inflammation and cardiovascular disease. "The time for taking action has now arrived," the authors wrote.
Reducing false positives could decrease the frequency of unnecessary procedures, lower the associated costs and also ease patient anxiety concerning CT results.
Evaluating LVDF with echocardiography or AI-powered electrocardiography can help identify individuals at an increased risk of developing atrial fibrillation, according to new data presented at the ASE 36th Annual Scientific Sessions.