MedTech News
Stereotaxis gets FDA nod for next-gen GenesisX surgical robot
Stereotaxis (NYSE:STXS) announced today that it received FDA 510(k) clearance for its next-generation GenesisX surgical robot.
Tandem wins FDA nod to pair Mobi pump with Android smartphones
Tandem Diabetes Care (Nasdaq:TNDM) announced today that it received FDA approval for the Android version of its Mobi mobile app
‘Smart’ shirt monitors and detects epileptic seizures in real time
Epilepsy is the world’s most common chronic neurological condition, affecting about 1 in every 100 people. Those who have it go into seizures of varying intensity, ranging from barely noticeable to dramatic, with convulsions and loss of consciousness.
AI beats traditional methods in prison-community disease control
Stanford Health Policy researchers built a model to test whether AI could effectively manage disease spread between prisons and surrounding communities. The results were decisive.
AI-optimized trial shows mental health app can ease university student distress
Researchers from Deakin University, Black Dog Institute and UNSW have completed an AI-optimized trial testing digital mental health interventions for university students experiencing psychological distress.
Ultrasound could help clear brain debris after stroke
A low-intensity ultrasound treatment clears neurotoxic debris from the brains of mice with induced bleeding that resembles a hemorrhagic stroke, according to a study published in Nature Biotechnology.
New imaging probe helps track prostate cancer and possibly treat it before resistance develops
Researchers at Wayne State University and the Barbara Ann Karmanos Cancer Institute have developed a chemical imaging probe that resists the breakdown of certain compounds in the body, giving doctors a more dependable way to track and potentially treat prostate cancer.
AI model powers skin cancer detection across diverse populations
Researchers at the University of California San Diego School of Medicine have developed a new approach for identifying individuals with skin cancer that combines genetic ancestry, lifestyle and social determinants of health using a machine learning model. Their model, more accurate than existing approaches, also helped the researchers better characterize disparities in skin cancer risk and outcomes.