News

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

The NIH Common Fund’s Bridge to Artificial Intelligence program launched this month, aiming to bridge the gap between biomedical and behavioral research and artificial intelligence.

NCI’s Small Business Innovation Research Development Center released four new contract funding topics. The topics aim to advance work in the fields of wearable technologies, digital tools, and artificial intelligence.

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

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.

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.

Data scientists, informaticists, and medical physicists are invited to develop the best, most generalizable models, algorithms, and approaches for breast density estimation using image-based distributed or federated learning.

IMPROVE focuses on improving deep learning models to predict the efficacy of cancer treatments. The research community, including data scientists and informaticists, is asked to respond to an RFI for creating protocols to evaluate model performance by April 15, 2022, at 5:00 p.m. ET. Additionally, they are encouraged to respond to an RFP for improving model comparison by May 9, 2022.

Over the past several years, scientists have made exciting advances in the realm of artificial intelligence (AI) and its integration into the cancer imaging field. New AI tools could make cancer imaging faster, more accurate, and more informative. But are they ready for real-world implementation?

Do you work on a project funded by an active NIH grant? Is this project rooted in artificial intelligence, machine learning, and/or ethics components? Apply to this Notice of Special Interest by March 31, 2022.

NCI’s Office of Cancer Clinical Proteomics Research’s new blog highlights recent findings from scientists in the Clinical Proteomic Tumor Analysis Consortium. It describes a proof-of-concept approach to identifying fraudulent data in biological data sets.