News

Keep up with the latest news from the NCI Center for Biomedical Informatics and Information Technology (CBIIT) and the data science communities.

Automatic segmentation of the liver from CT scan of patient TCGA-DD-A1EH

New Artificial Intelligence and Medical Imaging Annotations Added to the NCI Imaging Data Commons

Explore a new interactive dashboard that includes data sets of advanced machine-generated segmentation of tumor and organ contents.

Artists conceptualization of a digital twin. Shows the mirrored image of two heads. The only difference is one head is filled in with dots whereas the second head has spaces missing.

New Report Spotlights Research Gaps and Future Directions for Digital Twins

Interested in digital twin technology? Read this report for a “reality check” on what is currently known about the technology and what’s still missing.

icon representing the NIH Common Fund

Create Educational Courses and Encourage the Use of Common Fund Data Sets

This Notice of Funding Opportunity will allow you to create and run a short course to educate early career researchers on using data sets available in NIH’s Common Fund.

Illustration of a man’s upper torso, highlighting the lungs. In the background are dots and dashes to signify data. Concept is used to show the value of data in assessing lung disease.

Deep Learning Model Helps Predict Lung Cancer

A new deep learning model, called CXR-Lung-Risk, proved useful in identifying people at risk for dying from lung cancer or other lung disease, based on a single X-ray image.

close-up of computer chip

Opportunity for Data Scientists to Apply for AI Codeathon

If you’re a data scientist interested in artificial intelligence and machine learning codeathons, apply for this opportunity to build a solution for cancer!

hands typing on a keyboard with abstract data screen overlaid

New NCI-Supported Platform for Open Data Challenges

Explore a resource that lets you search for data challenges that address areas of unmet medical need!

Data themed connectivity icons in background. Text reads, Request for Information

Deadline Extended: Tell Us if NCI Cancer Research Data Commons’ Data are Compatible with AI

NCI wants your input to help determine how compatible NCI’s Cancer Research Data Commons is with artificial intelligence applications. Explore this request for information to learn how to contribute!

Image shows a non-contrast low-dose chest CT scan. Three red dashed lines run across the chest scan and show the sections selected for body composition assessment.

Using AI to Assess Body Composition Could Help in Cancer Care

In a recent study, NCI-funded researchers applied an artificial intelligence model to lung screening computed tomography images to assess body composition. The team used two key indicators of health—skeletal muscle and fat (adipose) tissue—to predict death from lung cancer, cardiovascular disease, and other causes.

Example of a scan using a non-invasive imaging technology. The scan shows a yellow band at the top, a green layer in the middle, and a deep blue band underneath. The colored layers represent skin and the underlying tissues.

NCI SBIR Award Helps Company Use AI to Assess Cancerous Skin Lesions

With the help of an NCI SBIR grant, Enspectra Health, Inc., is blending deep learning algorithms with existing imaging technology to create a new way of obtaining a virtual biopsy.

Silhouette image of of side portrait faces of five people that overlay each other. Three of the portriat faces are colored in light, medium and dark shades of red, one is in black and the last is shaded in torquise color.

Addressing Racial and Ethnic Bias in Algorithms that Predict Colorectal Cancer Risk

NCI-funded researchers looked at the impact of racial and ethnic bias on algorithms that help clinicians make more informed decisions when caring for patients with colorectal cancer. They found that removing the race and ethnicity variable could lead to higher bias in the model’s performance.

SUBSCRIBE TO UPDATES

Categories

Archive