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
If there were an unofficial theme of SIR 2024, it might be artificial intelligence—what it is, when to use it and where it might go next. From dedicated sessions to keynote lectures, the possibility of AI and robotics in interventional radiology was a frequent discussion. According to Bruce J. Tromberg, AI is changing the way physicians practice medicine. Source: SIRToday
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.