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
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