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CBIIT Cancer Data Science Pulse Blog

A data science blog featuring news and updates from CBIIT.  

  • Professional headshot of Dr. Umit Topaloglu positioned on the right while text on the left reads: Q&A federated data in cancer research
    Questions Answered: Federated Learning in Cancer Research
    • By Umit Topaloglu, Ph.D.

    How are cancer researchers using federated learning? NCI CBIIT’s Dr. Umit Topaloglu answers this and other frequently asked questions about this topic.

  • Promotional image text on the left and headshot of Dr. Juli Klemm on the right. The text reads: Q&A Informatics and IT in cancer research
    Questions Answered: Informatics and IT in Cancer Research
    • By Juli Klemm, Ph.D.

    How do informatics and IT enable NCI research? Acting NCI CBIIT director, Dr. Juli Klemm, answers this and other frequently asked questions about technology in cancer research.

  • A young white male laying flat, entering an MRI machine.
    Applying Artificial Intelligence (AI) to Whole-Body Images to Reveal Rare Cancers

    Learn how AI-assisted whole-body imaging may someday help not only in detecting cancer, but also in planning, tracking, and managing more precise treatments.

  • ""
    Many Hands Make Light Work: Your Role on a Cancer Data Science Research Team
    • By Daoud Meerzaman, Ph.D., Tanna Nelson, Ph.D., R.N., NI-BC, Granger Sutton, Ph.D.

    A multidisciplinary team consists of many different responsibilities. Where do you fit in?

  • Spyglass hovers over a stream of circles containing illustrated headshots; signifies the idea of matching people to specific cancer treatments.
    Building Infrastructure that Works—Lessons Learned from Project MATCH
    • By Umit Topaloglu, Ph.D., Jacob Gross, Nicholas Renzette, Ph.D.

    NCI’s Project MATCH initiative helped pioneer the concept that people in clinical trials could be matched (based on their genetic makeup) to medications specifically tailored to their needs and situations.

  • 3d illustration of T cells attacking cancer cells. Shows a blue-colored cancer cell with two smaller red cells attached.
    NCI’s IMMUNOtron—The Making of a Machine Learning (ML) Robotics Tool
    • By Grégoire Altan-Bonnet, Ph.D., Sooraj Achar

    ML models feed on large amounts of quality data, which can be scarce. Meet IMMUNOtron, a ML-robotic platform that’s helping NCI researchers generate and process high-quality data to better understand the immune system’s response to cancer.

  • Brightly colored cloud is surrounded by question marks. Depicts the idea, "Is the Cloud for me?"
    Using the Cloud for Cancer Research—Overcoming Common Barriers
    • By Zhaoyi Chen, Ph.D.

    Learn tips for overcoming obstacles using the cloud, along with an example of how you can make the cloud work for you.

  • Numerical data points within a heart graphic, surrounded by other hearts. All shades of blue.
    Whose Data Is It, Anyway?
    • By Joe Flores-Toro, Ph.D., Mousumi Ghosh, Ph.D.

    The Office of Data Sharing discusses data ownership and data sharing resources for supporting research.

  • Artists conceptualization of a digital twin. Shows the mirrored image of two heads. The only difference is one head is filled in with dots whereas the second head has spaces missing.
    Digital Twins for Cancer—Not If, But When, How, and Why?
    • By Eric Stahlberg, Ph.D.

    Creating a digital twin for cancer is a daunting task, but NCI’s Dr. Eric Stahlberg says we already have many elements in place to serve as a digital twin foundation. All that’s needed now is a shift in thinking and a team science approach to bring a true cancer digital twin to life.

  • interconnected data points forming the shape of an open laptop with a gear and a wrench icon overtop
    Making a Bioinformatics Tool for the Cancer Research Community
    • By Daoud Meerzaman, Ph.D.

    Discover how to make your bioinformatics tools more broadly usable with no-code solutions!

  • Image of a small square that reads "AI" in white, with larger letters reading "AI" above it floating in the air. Blue bacground.
    Semantics Series—The Role of Common Data Elements and Artificial Intelligence
    • By Denise Warzel, M.Sc.

    Common Data Elements (CDEs) enrich and standardize data through consistent and accurate metadata, helping to make data ready for use in training artificial intelligence (AI) models. In this blog, Ms. Denise Warzel discusses the role of CDEs and AI in CBIIT’s Semantic Infrastructure.

  • Scale set against a background of high-tech imagery, including a bright circle and smaller lines connected by dots. Denotes the idea of bringing balance to biomedical data sets.
    Synthetic Data Helps Counter Lack of Diversity in Data
    • By Laritza Rodriguez, M.D., Ph.D.

    In this blog, NCI’s Center for Cancer Health Equity, Dr. Laritza Rodriguez, looks at one technique to help counter a lack of diversity in your data set. See how Synthetic Minority Oversampling Techniques (SMOTE) can help bring your biomedical research data into better balance.

  • Three circles depict three separate but connected events. The first features a researcher looking at medical scans, the second is a team gathered around a laptop, and the third shows a doctor with a patient.
    A Quick Start Guide to Cancer Data Science for Clinical Oncology
    • By CBIIT Staff

    Whether you are in the data science field, interested in developing computational solutions for clinical oncology, or a clinical researcher, we’ve curated a list of data sets, tools, and learning resources to showcase how these disciplines can and are working together to empower cancer research.

  • A person wearing a stethoscope holds a tablet with one hand and presses the screen with the other. The letters A-I are illuminated above the screen, depicting how doctors and researchers are using AI to address today’s biomedical issues.
    The Good, the Bad, and the Unexplained: 5 Tips for Evaluating an AI Product
    • By Baris Turkbey, M.D., Stephanie A. Harmon, Ph.D.

    Are you interested in using artificial intelligence (AI) in your research or clinical practice but feeling unsure about where to start? Researchers from NCI’s Center for Cancer Research, Drs. Baris Turkbey and Stephanie Harmon, offer five tips that can get you started.

  • several pictures representing various ambiguous terms in cancer and data science including a person playing a video game, hot peppers, DNA sequencing, a graph, and a child watching a cartoon.
    Hone Your Communication Skills: “Weird” Cancer and Data Science Terms
    • By CBIIT Staff

    Explore some of the interesting terms used in cancer research and data science, and get tips on how you can make sure you’re communicating effectively!

  • Tony Kerlavage
    Dr. Tony Kerlavage Reflects on His Time at NCI CBIIT
    • By Tony Kerlavage, Ph.D.

    Following 13 years at NCI and seven years as CBIIT’s director, Dr. Kerlavage plans to retire at the end of May. He shares his experience serving as director, advice for the future director, and plans for his retirement.

  • Button with the words "Edge Computing" in the center and surrounded by icons that are important for this technology. These icons include a person (to signify the user), a lightbulb (to show an idea), a spyglass (to show research or questions), a hand with dollar signs (to show economics), a graph (to show how research is used to yield solutions), and a series of lines and cogs (to show how the system works).
    Living on the Edge—How Video Games Helped Shape the Future of Cancer Care
    • By Eric Stahlberg, Ph.D.

    Did you know that the same technology that makes your video games more realistic is helping to power important advances in cancer research? This latest blog by Dr. Eric Stahlberg looks at edge computing and how it’s helping to transform cancer research and care.

  • Image of a small square that reads "AI" in white, with larger letters reading "AI" above it floating in the air. Blue bacground.
    Semantics Series—A Deep Dive Into Common Data Elements
    • By Denise Warzel, M.Sc., Gilberto Fragoso, Ph.D.

    Common Data Elements (CDEs) are a key component of NCI’s semantics infrastructure. CDEs allow us to assign meaning to data in a way that’s predictable, consistent, and persistent across time. CBIIT’s Ms. Denise Warzel and Dr. Gilberto Fragoso show how CDEs help researchers define, map, and use data more efficiently.

  • A Magnetic Resonance Image (MRI) on the left (A) shows a suspicious cancer lesion (dark mass marked by arrows). A deep learning-based AI algorithm helps further define this lesion as prostate cancer (B). The lesion in B is displayed as a large red mass, outlined in blue and green. The lesion in B is much larger than the one shown in A, indicating AI helped to better define the extent of the cancer than MRI alone.
    Theranostics and AI—The Next Advance in Cancer Precision Medicine
    • By Baris Turkbey, M.D.

    In this blog, Dr. Baris Turkbey, senior clinician in NCI’s Molecular Imaging Branch, Center for Cancer Research, explores the field of theranostics. He describes how artificial intelligence and data are helping researchers “see” cancer in a new way, resulting in a more precise way of targeting cancer treatment.

  • Photo of a DNA double helix overlaid with binary code (ones and zeros) and DNA sequence TCGA.
    Trusting the Data—A Look at Data Bias
    • By Vivian Ota Wang, Ph.D.

    Dr. Vivian Ota Wang shares her perspectives on data bias and outlines ideas for making data more equitable, fair, and useful to the greatest number of people, all of which would benefit cancer research.

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