Emphasis
The emphasis is on development of transformative machine intelligence-based systems, emerging tools, and modern technologies for diagnosing and recommending treatments for a range of diseases and health conditions. Unsupervised and semi-supervised techniques and methodologies are of particular interest.
Program priorities and areas of interest:
- clinical decision support systems
- computer-aided diagnosis
- computer-aided screening
- analyzing complex patterns and images
- screening for diseases
- natural-language processing and understanding
- medical decision-making
- predictive modeling
- computer vision
- robotic and image guided surgery
- personalized imaging and treatment
- drug discovery
- radiomics
- machine/deep learning-based segmentation, registration, etc.
Additional support
This program also supports:
- early-stage development of software, tools, and reusable convolutional neural networks
- data reduction, denoising, improving performance (health-promoting apps), and deep-learning based direct image reconstruction
- approaches that facilitate interoperability among annotations used in image training databases
Related News
A team of engineers led by the University of Massachusetts Amherst and including colleagues from the Massachusetts Institute of Technology (MIT) recently announced in the journal Nature Communications that they had successfully built a tissue-like bioelectronic mesh system. The mesh can grow along with the cardiac cells, allowing researchers to observe how the heart's mechanical and electrical functions change during the developmental process.
Many companies are now developing isothermal genetic tests that can diagnose a wide array of respiratory diseases, sexually transmitted infections and more. These products aim to provide precise and prompt diagnostic information, enabling people to quickly seek appropriate medical treatment. Source: Nature
UMass Chan Medical School researchers have documented a phenomenon that had confounded clinicians: Some people persistently test positive for SARS-CoV-2, the virus that causes COVID-19, on rapid home antigen tests despite obtaining concurrent negative PCR tests. Source: Medical Xpress