Artificial Intelligence, Machine Learning, and Deep Learning
This program supports the design and development of intelligent and innovative algorithms, software, methods, and computational tools to enhance analysis of complex medical images and data. Relevant technologies include those that facilitate organization, representation, retrieval, analysis, recognition, and classification of biomedical and biological data and images.
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
- machine/deep learning-based segmentation, registration, etc.
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