Learn how artificial intelligence is helping researchers model cancer risk and enhance cancer research.

During the SNO/NCI joint event, “Introduction to Career Pathways in Neuro-Oncology,” CBIIT’s Dr. Jill Barnholtz-Sloan will present “#DataMatters in neuro-oncology” to share the importance and impact of data science on central nervous system neoplasm research.

In this talk, Mrs. Aya Abdelsalam Ismail will give an overview on interpreting Deep Neural Networks (DNNs), focusing on the use of DNNs to track and predict changes over time.

Join the December NCI Imaging and Informatics Community webinar to learn how Dr. Martin Yaffe’s team is developing imaging tools and a multi-platform approach to improve breast cancer detection and diagnosis.

In this webinar, Drs. Mancini and Gilmore will describe how different types of biomarkers (including those retrieved by a patient wearable) can be used to examine the effects of cancer and cancer treatment on trajectories related to aging. Examples include digital biomarkers related to gait and balance, as well as a biological biomarker reflecting epigenetic age.

Hear from Columbia University’s Dr. Elham Azizi as she presents a set of machine learning methods developed to address problems such as handling sparsity and noise, distinguishing technical variation from biological heterogeneity, inferring underlying circuitry, and inferring temporal dynamics of immune cell states in clinical cohorts. Dr. Azizi will also present novel biological insights obtained from applying these methods to cancer systems.

In this talk, Dr. James Lacey will describe the choices the cancer research community should consider and the questions they need to ask when transitioning their research projects to a cloud-based ecosystem.

Join the upcoming NCI Genomic Data Commons’s (GDC) monthly webinar to learn how to download and upload genomic data to the GDC.

Attendees of the 2021 Radiological Society of North America’s Annual Meeting can stop by the NCI Imaging Data Commons’ educational exhibit to learn more about its capabilities and plans for continued development.

In this talk, Dr. David Kepplinger will describe the detrimental effects of “data-artifacts,” specifically as they relate to biomarker discovery and related feature selection techniques. He will also discuss a novel method for reliably identifying relevant biomarkers in the presence of such artifacts.