301-451-6771
shabestb@mail.nih.gov
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
Researchers have established an RNA-based method that drives cells in the body to produce therapeutic proteins and secrete them into the bloodstream. The approach could extend the lifespan of drugs in the body, reducing the burden on patients.
Artificial intelligence models often play a role in medical diagnoses, especially when it comes to analyzing images such as X-rays. However, studies have found that these models don’t always perform well across all demographic groups, usually faring worse on women and people of color. Source: Massachusetts Institute of Technology News
A team of researchers led by the University of California San Diego has developed a soft, stretchy electronic device capable of simulating the feeling of pressure or vibration when worn on the skin. The new technology could pave the way for the development of advanced devices in virtual reality, medical prosthetics and wearable technology. Source: University of California San Diego.
The FDA granted marketing authorization for Cepheid’s Xpert HCV test and GeneXpert Xpress System, the first rapid test for hepatitis C virus intended for use in point-of-care settings. Source: Helio
Biomedical engineers at Duke University have developed a new technique to better understand and test treatments for a group of extremely rare muscle disorders called dysferlinopathy or limb girdle muscular dystrophies 2B (LGMD2B). The approach grows complex, functional 3D muscle tissue from stem cells in the laboratory, creating a platform that replicates patient symptoms and treatment responses. Source: Duke University