Cancer Data Science Pulse

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Artist's rendition of data and artificial intelligence. Shows a small blue circle with a big smile to represent data and an orange rectangle with an antenna on top, also smiling, to represent AI.

Datum and Artificial Intelligence—A Perfect Match

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.

Aya Abdelsalam Ismail

Did the Machine Get it Right? Learning to Trust Neural Networks in Medical Applications

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.

Illustration of a digitally rendered cell.

Meteorology, Aerospace Engineering, and Cancer Research—The Future of Predictive Modeling

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.

Imaging Data Commons website portal featuring a radiology image and a graph chart, Cases by Major Primary Site. Chest has the most, then brain, head and neck, breast.

Imaging Data Commons Brings the Power of the Cloud to Cancer Research

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.

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