Cancer Data Science Pulse

Read the blogs that topped our charts in 2022 and see if your favorite made #1!

Learn more about new streamlined access to broad-use data sets within the database of Genotypes and Phenotypes (dbGaP).

In honor of National Lung Cancer Awareness Month, we’re highlighting the “data deets” (details) for the National Lung Screening Trial, a large-scale effort that collected imaging data for more than 53,000 heavy smokers. In this blog, we’ll cover the research that drove this data, specific metrics about the data set, how to access it, and some of the exciting data science projects using the data.

Data and Artificial Intelligence (AI) are a match seemingly made in heaven. By joining data and AI, scientists are able to shift a lot of the burden associated with using data from human to machine. See why the data-AI relationship works so well for cancer research in this offbeat blog featuring two fictitious characters—Datum and his pal Aida.

In this blog, University of Maryland's Mrs. Aya Abdelsalam Ismail examines the use of Deep Learning in medical applications, especially as a means for following a disease or disorder over time. She’ll describe how a “wrong turn” in her research on forecasting Alzheimer’s Disease led her to question her model’s performance. Her findings are particularly relevant for Deep Learning models in the cancer field, which use images obtained from patients, often at different points in time.

What do winter storms, airplanes, and cancer research have in common? In this blog, experts on meteorology, aerospace engineering, and radiation oncology explore what we can learn from these very different fields to further advance how we target and apply radiation to more effectively treat cancerous tumors.

On October 20th, NCI launched the Imaging Data Commons (IDC), the latest data repository to be offered within the Cancer Research Data Commons (CRDC) infrastructure. Through the IDC, both researchers and clinicians will have access to a wide range of cancer-related images, including radiology and pathology imaging data, as well as their accompanying metadata.