3 Questions: What does innovation look like in the field of substance use disorder?
Hanna Adeyema and Carolina Haass-Koffler discuss the substance use disorder crisis and the future of innovation in the field.
Hanna Adeyema and Carolina Haass-Koffler discuss the substance use disorder crisis and the future of innovation in the field.
“ScribblePrompt” is an interactive AI framework that can efficiently highlight anatomical structures across different medical scans, assisting medical workers to delineate regions of interest and abnormalities.
The software tool NeuroTrALE is designed to quickly and efficiently process large amounts of brain imaging data semi-automatically.
A mathematical method, validated with experimental data, provides a fast, reliable, and minimally invasive way of determining how to treat critical blood pressure changes during surgery or intensive care.
Genomics and lab studies reveal numerous findings, including a key role for Reelin amid neuronal vulnerability, and for choline and antioxidants in sustaining cognition.
The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.
Propofol, a drug commonly used for general anesthesia, derails the brain’s normal balance between stability and excitability.
This tiny, biocompatible sensor may overcome one of the biggest hurdles that prevent the devices from being completely implanted.
Three innovations by an MIT-based team enable high-resolution, high-throughput imaging of human brain tissue at a full range of scales, and mapping connectivity of neurons at single-cell resolution.
MIT neuroscientists have found that the brain uses the same cognitive representations whether navigating through space physically or mentally.
By capturing short-lived RNA molecules, scientists can map relationships between genes and the regulatory elements that control them.
New adhesive hydrogel coatings could prolong the lifespan of pacemakers, drug delivery depots, and other medical devices.
By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.
MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.
MIT neuroscientists have discovered a circuit that controls vocalization and makes sure that breathing is prioritized over speaking.