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

NCI-funded researchers used artificial intelligence to develop an accurate cancer estimation map for defining tumor margins. They found their model outperformed conventional estimates of tumor margins using imaging alone.

Using Artificial Intelligence to Map Prostate Tumors

NCI-funded researchers used artificial intelligence to develop an accurate cancer estimation map for defining tumor margins. They found their model outperformed conventional estimates of tumor margins using imaging alone.

Pathology image of H&E stained slide showing colorectal cancer

New AI Tool Helps Interpret Pathology Slides to Predict Cancer Recurrence

NCI-funded researchers combined long-term, patient-outcome data with pathology slides from people with colorectal cancer to develop a machine learning tool, called QuantCRC. Using QuantCRC, researchers could predict if a patient’s cancer would recur based on analysis of a single hematoxylin and eosin stained slide of the tumor.

Data points and lines are used to illustrate the figure of a woman, with highlighted circles to indicate breasts and the acronym “AI” appearing at the top.

New Deep Learning System Proves Accurate in Predicting Suspected Breast Cancer

A new, NCI-funded, deep learning technology performed on par with radiologists in interpreting breast cancer images. This tool could help refine diagnosis to reduce the number of unnecessary biopsies.

MRI image of the prostate showing segmentation of the core and peripheral zones.

New Contract Opportunity to Obtain Medical Image Segmentations

NCI is seeking support for developing machine-generated segmentations of images in the radiology collections of the Imaging Data Commons (IDC). Submit your proposals by March 10, 2023.

Figure shows CT scans and corresponding 3-D renderings of tumor vasculature for people who responded to therapy vs. those who didn't. Tumor vasculature in non-responders had more twists and turns than those who responded to treatment.

Tumor Twistedness Serves as AI-Based Biomarker for Lung Cancer Immunotherapy

Using data from routine lung scans, NCI-supported researchers developed an AI-based tool to help predict how patients will respond to therapy.

Illustrated cloud with three small squares displayed in front of it. The squares represent different repositories stored within the cloud.

New Data Set from the National Clinical Trials Network Includes Pediatric Brain Tumor Imaging

This newly released data set provides imaging in pediatric patients with newly diagnosed primitive neuroectodermal tumors throughout their treatment and until any potential relapse.

Childhood cancer patient trying to listen to the heartbeat of their teddy bear with a stethoscope.

See What’s New in the Childhood Cancer Data Catalog

The latest update to the Childhood Cancer Data Catalog includes website improvements and the addition of the database of Genotypes and Phenotypes (dbGaP).

Blue torso and lungs with red-orange cancer spot. Text that says "AI"

Observational Study Shows Value in Using AI to Plan Radiotherapy for Lung Cancer

Learn how NCI CT (Computed Tomography) imaging data sets enable the use of artificial intelligence in planning treatment for non-small cell lung cancer.

AI on blue data science background

NCI-Supported Study Uses Deep Learning for Cancer Prognosis

An NCI training grant and resources such as the NCI Cancer Research Data Commons’ Genomic Data Commons, in part, made it possible for this study to use multimodal deep learning. This model allowed researchers to examine pathology whole slide images and molecular profile data from 14 cancer types to enable more accurate patient outcome predictions.

The letters AI on a blue background with white interconnected dots.

AI-Driven Software Based Off NIH Algorithm Receives FDA Clearance in Detection and Diagnosis of Prostate Cancer

An artificial intelligence (AI)-driven, computer-aided diagnosis (CAD) software first developed by code writers’ physicians at NIH has received FDA clearance for the detection and diagnosis of prostate cancer. The tool, called ProstatID, combines AI with traditional MRI scanning.

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