Carlsmed earns Medicare win for AI-powered spine implants
August 1, 2025
Carlsmed (Nasdaq:CARL) today announced new technology add-on payment (NTAP) reimbursement for its spine implant technology.
Carlsmed (Nasdaq:CARL) today announced new technology add-on payment (NTAP) reimbursement for its spine implant technology.
To diagnose either type 2 diabetes or pre-diabetes, clinicians typically rely on a lab value known as HbA1c. This test captures a person’s average blood glucose levels over the previous few months. But HbA1c cannot predict who is at highest risk of progressing from healthy to prediabetic, or from prediabetic to full-blown diabetes.
Modern medicine is largely reactive—treating illness only after symptoms emerge. But a new study from the Research Institute of the McGill University Health Center (The Institute) and McGill University points to a more proactive future: one where silent signs of infection are detected before we even feel sick.
A personalized brain stimulation system powered by artificial intelligence (AI) that can safely enhance concentration from home has been developed by researchers from the University of Surrey, the University of Oxford and Cognitive Neurotechnology. Designed to adapt to individual characteristics, the system could help people improve focus during study, work, or other mentally demanding tasks
Dexcom (Nadsaq:DXCM) announced today that it released a new AI-powered photo meal logging feature for its Stelo platform.
Researchers have harnessed the power of artificial intelligence to design a blueprint for building a vaccine that aims to teach the body’s immune system to fight cancer.
A new study from the University of Colorado Anschutz Medical Campus shows that free, open-source artificial intelligence (AI) tools can help doctors report medical scans just as well as more expensive commercial systems, without putting patient privacy at risk.
Johnson & Johnson (NYSE:JNJ) announced today that the FDA granted priority review to a new drug application (NDA) for its TAR-200.
Artificial intelligence (AI) models trained on large datasets are increasingly seen as the key to unlocking personalized treatments for brain disorders. An important bottleneck for scaling AI is the cost of data collection. This raises a fundamental dilemma: is it more cost-effective to scan more people for a short time, or fewer people for longer?
With the help of artificial intelligence (AI), an inexpensive test found in many doctors’ offices may soon be used to screen for hidden heart disease.