News

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

The letters "A.I." hover overtop a keyboard. A finger checks the first of three boxes that appear to the right. Image signifies the importance of adhering to guidelines when developing artificial intelligence.

NCI Helps Establish Guidelines for Artificial Intelligence (AI) Models for Prostate Cancer

Having trouble discerning what makes a successful AI model? NCI is leading the way in developing concrete guidelines for building, evaluating, and reporting on AI-assisted prostate imaging models.

AI themed image with connected data points and a silhouette of a head with "AI" in the brain area

Important Reminders About the Use of AI and Protecting Human Genomic Data

If you use or develop generative artificial intelligence (AI) in your cancer research, these important reminders about data security are for you!

Spyglass hovers over a strand of double helix strand of DNA.

NCI-Funded Pipeline Applied to Microscopic Images Helps Manage Micronuclei

See how a new AI-driven tool can help you measure micronuclei and similar structures to study their underlying biology, enabling you to more efficiently measure and characterize these tiny structures.

Head with the letters “A.I” shows how AI can help “see” research in a new way. The head is focusing on icons that represent pathology, research, imaging, and ideas—all of which come together to create a new perspective for cancer research.

The Making of a New Artificial Intelligence (AI)-Approach to Head and Neck Cancer

See how NCI-funded researchers built on previous studies to create a new model (called SMuRF) for head and neck cancer. Their model offers a new, more human-like, perspective to assessing head and neck cancer.

Two hands shaking, with the letters “AI” in the forefront. Signifies a new public-private partnership using artificial intelligence.

NCI Clinical Trials Get a Boost from Public-Private Partnership

Read about a new collaboration between NCI and a company that develops AI-powered solutions for cancer diagnostics and therapeutics. NCI will be applying these tools to help advance research into personalized treatment for patients with cancer.

Person sits at a laptop and presses a file. The file opens four documents with a background that shows charts, flow charts, and additional buttons. Signifies the idea of an online resource.

NCI-Supported Study Uses Machine Learning (ML) to Help You Tap into the TCGA

Thanks to this NCI-funded study, you now have a host of top-performing predictive models, data types, and training algorithms to help you better classify your patient samples.

AACR Annual Meeting

NCI Data Science at the 2025 AACR Annual Meeting

See when and how you can access NCI’s data science sessions at the 2025 American Association for Cancer Research Annual Meeting!

person in a lab coat, working in a lab on a computer.

FusOn-pLM: A Fusion Oncoprotein-Specific Language Model for Predicting Drug-Resistant Mutations

Do you work with fusion oncoproteins? Explore a new protein language model (pLM) that NCI-funded researchers trained on fusion oncoproteins to advance discoveries in fusion-driven cancers!

holographic icons representing various types of medical imaging data, with a person with a finger raised to tap one.

Validate and Test your DICOM De-Identification Algorithms Using the MIDI Benchmark

Use the Medical Image De-Identification Benchmark (MIDI-B) to assess the effectiveness of your DICOM image de-identification tool or algorithm. MIDI-B provides a platform for you to measure the automated removal of protected health and personally identifiable information from medical images.

3D illustration of an upper torso showing spine, lungs, and heart. A popup image of lung cancer shows what a cancerous tumor looks like under a microscope.

Deep Learning Model CGS-Net Enhances Medical Image Analysis

Learn how CGS-Net can assist in diagnosing cancer by incorporating contextual information for more accurate segmentation in medical images.

SUBSCRIBE TO UPDATES

Categories

Archive