AuntMinnie
APRIL 10, 2025
Congress aims to establish a steady reimbursement pathway for medical devices authorized by the U.S. A new bill introduced in the U.S. Food and Drug Administration (FDA) that use AI and machine learning, including those used in radiology. The Health Tech Investment Act (S. 1399) was introduced by Senator Mike Rounds (R-SD) on April 9.
Health Imaging
DECEMBER 1, 2023
Cybersecurity consultant Richard Staynings argued legacy medical devices are inherently insecure—and likely to remain in hospitals for decades to come.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
AuntMinnie
NOVEMBER 18, 2024
While academic medical center radiology departments are expanding significantly and hospitals are adapting to health system consolidation trends, demand for innovative imaging informatics remains strong among operations and physician teams. Another, a new hospital complex is underway at University of Utah Health.
AuntMinnie
MARCH 19, 2024
France-based medical device developer inHeart has received clearance from the U.S. While the software has been commercially available to clinicians in Europe, FDA clearance now allows inHEART to market the product to hospitals across the U.S. Food and Drug Administration (FDA) for its AI-driven digital twin of the heart.
AuntMinnie
MAY 9, 2024
Centers for Medicare and Medicaid Services (CMS) has also provided some reimbursement through Category I codes and the Hospital Outpatient Prospective Payment System (HOPPS). It remains unclear, however, that all reimbursed uses are currently adding value to patients or the health system, Thorwarth said.
AuntMinnie
NOVEMBER 9, 2023
If this deep-learning model becomes available as a medical device, chest x-rays taken in a variety of settings, such as medical examinations, checkups, and hospitals, could be used to screen for osteoporosis,” Sato and colleagues suggest. The model achieved 79% accuracy, 96.6% sensitivity, and 34.1% accuracy, 77.1%
AuntMinnie
JULY 25, 2024
Researchers led by Seyed Tabatabaei, MD, from Massachusetts General Hospital and Harvard Medical School in Boston, in their clinical perspective outlined these pitfalls and made suggestions on AI model training and validation, as well as using diverse datasets.
Expert insights. Personalized for you.
288 
Let's personalize your content