Sensitive data removal is critical to medical image sharing. Attend this two-day workshop to learn more about this topic and the role data science plays in de-identifying the data.
Eric Stahlberg, Ph.D., Sunita Menon, and Ishwar Chandramouliswaran
NIH/NCI representatives will take part in this year’s Bio-IT World Conference & Expo, which showcases technologies and analytic approaches to accelerate science and drive the future of precision medicine. Check out their presentations if you want to learn more about “digital twins” and “FAIR” data!
In this webinar, Dr. Ma’ayan describes two new bioinformatics software tools he and his lab are developing. Learn how these data-integration tools can help in analyzing a variety of data types to better understand complex diseases, such as diabetes and cancer.
If you’re interested in how data plays a part in understanding sex differences in cancer, be sure to hear Jill Barnholtz-Sloan at this upcoming conference!
Interested in using quantitative imaging methods in preclinical and clinical trial settings? Attend this virtual meeting to network with others and to learn more.
Dr. Tolga Can of the Colorado School of Mines will discuss how he and his colleagues at Erson-Bensan Lab are using publicly available RNA-seq data sets and Cancer Genomics Cloud resources to screen for alternative polyadenylation events in cancer cells.
Want to learn more about data sharing and reuse practices that could be applied to your cancer research? This symposium will have a range of data science panels for you to choose from!
Hear from NCI’s Associate Director for Informatics and Data Science Program and learn about the intersection of data science and the future of cancer research.
Nadia Howlader, Ph.D., Angela Mariotto, Ph.D., and Annie Noone, Ph.D.
Curious about how COVID-19 impacted cancer diagnosis? Register for this webinar, where speakers will discuss examples of the 2020 data point in SEER*Explorer.
Join the April Imaging and Informatics Community Webinar and hear Mayo Clinic’s Dr. Tim Leiner discuss the applications of machine learning in cardiovascular imaging. Some of the methods presented will have applications in cardiac evaluation of patients undergoing cancer immune- or chemo-therapies.
Find training resources, opportunities to collaborate, advice from NCI data science experts, and ways to network and engage with the cancer data science community on our NCI Cancer Data Science page!
