Despite the advancement of AI and machine learning technologies and their incorporation into cancer treatment and drug development, a lack of trust and understanding of these new approaches is impeding care and treatment.
Royal Philips NV unveiled its Future Health Index report for 2025, and it reveals the widening trust gap between health care professionals and patients concerning the adoption of AI in health care.
The U.S. FDA typically announces its inspections at facilities located outside the U.S. – a courtesy not extended to domestic manufacturing sites. This is about to change per an agency press release quoting commissioner Marty Makary as describing the disparate treatment as a double standard.
The U.K. National Institute for Health and Care Excellence (NICE) opened a late-stage assessment for drug-eluting stents (DES) with an eye toward costs, advising clinicians that they should implant the least expensive DES unit that is clinically appropriate for that patient while the assessment is underway.
Seoul, South Korea-based Voinosis Co. Ltd. filed for potential worldwide protection of its AI-based system that allows for the early detection cognitive impairment, dementia, Alzheimer’s disease and hearing loss through voice analysis.
The Advanced Medical Technology Association released a policy proposal for AI in medical devices that took the U.S, FDA to task for its guidance for predetermined change control protocols for AI, stating that the guidance is “inconsistent with the statutory authority” for PCCPs.
In a roadmap to change animal testing requirements for INDs, the U.S. FDA said its new approach will improve drug safety, hasten the evaluation process, and lower costs for companies and patients. It’s another step in a process of changing rules put in place decades ago.
In a roadmap to change animal testing requirements for INDs, the U.S. FDA said its new approach will improve drug safety, hasten the evaluation process, and lower costs for companies and patients. It’s another step in a process of changing rules put in place decades ago.
AI could significantly improve the value of patient recalls following mammography, but so far radiologists seem reluctant to rely on computer-aided readings. Radiologists tend to trust their own judgment – and that of their colleagues – in mammogram readings far more than AI-based diagnostics, even when the AI is much more accurate, a prospective trial analysis published in Radiology by Karolinska Institutet researchers found.
The U.S. NIH published the results of a study of the use of AI in referring patients for intervention for risk of opioid use disorder, which found the algorithm helped stave off hospital admissions.
