Cancer Data Science Pulse

Artificial Intelligence
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.

Cartoon-style people in a lab, one male sitting at desk looking at computer, one female standing up looking at a tablet, another male standing up looking through a magnifying glass at an atom. A chemical compound drawing is behind them on the wall.

Five Data Science Technologies Driving Cancer Research

To commemorate the National Cancer Act’s 50th anniversary, we’ve pulled together Five Data Science Technologies poised to make a difference in how cancer is diagnosed, treated, and prevented.

Dr. Yanjun Qi

Computer Savvy Scientist Blends Technology with Biology to Create Attention-Based Deep Learning Methods for Genomics Data

On Wednesday, September 22, 2021, Yanjun Qi, Ph.D., from the University of Virginia, will present “AttentiveChrome: Deep Learning for Predicting Gene Expression from Histone Modifications,” in the kickoff of the Fall Data Science Seminar Series. This blog offers insight on Dr. Qi’s research and why this topic is important to her.

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.

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