Artificial Intelligence, Machine Learning, and Deep Learning


Supports the design and development of artificial intelligence, machine learning, and deep learning to enhance analysis of complex medical images and data.


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

    April 23, 2024

    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

    April 11, 2024
    NIBIB-supported researchers have developed a smart nanoprobe designed to infiltrate prostate tumors and send back a signal using an optical imaging technique known as Raman spectroscopy. The new probe, evaluated in mice, has the potential to determine tumor aggressiveness and could also enable sequential monitoring of tumors during therapy to quickly determine if a treatment strategy is working.
    April 5, 2024
    NIBIB is marking the 10-year anniversary of a commercialization program that helps innovators bring their medical devices from the lab to the marketplace.
    March 28, 2024
    A photo of a thin silicon pacemaker device
    While pacemakers have treated many patients with heart rhythm disorders, their bulky design and use of wires limits their usefulness and poses a risk of heart damage or infection. Now, researchers have cut the cords, shrunk the size, and expanded the capabilities of current designs.
    March 26, 2024

    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.

    Source: University of Massachusetts Amherst