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Keep up with the latest news from the NCI Center for Biomedical Informatics and Information Technology (CBIIT) and the data science communities.

Multimodal image of cancer tumor cells shows how the Orion tool is able to combine two types of images—hematoxylin and eosin and immunofluorescence—in a single slide.

NCI-Funded Tool Combines Imaging Modalities to Aid Pathologists and Machine Learning (ML)

An NCI-funded technology blends specific molecular markers along with traditional morphological features in the same cells and in one digital slide. This tool could someday help pathologists and ML models better predict cancer treatment response and outcomes.

A hand is holding a tablet. Illuminating from the table is the image of a clock. This abstract image conveys how technology is helping monitor disease and predict the course of cancer over time.

AI, Genomics, and Clinical Data Help Track Cancer’s Evolution Over Time

An international team of researchers combined genomics, biopsy results, and artificial intelligence (AI) to track prostate cancer over time. Learn more about these “evolvability” metrics and how they could someday help predict cancer re-occurrence.

Image displays timeline of diverging treatment schedules seen for different patients. 1. is a computer with a data chart. 2. Data from patients goes into the cloud. 3. Data is analyzed. 4. Treatment options are produced based on data research.

NCI Study Shows Promise of Machine Learning’s Role in Personalized Cancer Treatment

NCI-funded researchers are blending mathematics with machine learning to refine cancer treatment. In the future, this kind of virtual tumor model could help to further personalize care for people with cancer.

MRI image of an enlarged prostate.

NCI Uses AI to Take the Guesswork Out of Assessing Prostate Cancer Images

NCI researchers are using artificial intelligence (AI) to uncover additional information from medical images. This helps them not only to diagnose cancer but also to predict how it will progress and if it will re-occur.

A strand of DNA is shown inside a brightly colored circle. A second circle highlights a portion of the DNA and is designated by an “+”. Depicts how high-tech tools are being used to better understand genetics.

Machine Learning Approach Helps Interpret Genome-Wide Dynamics

A new, scalable, machine learning model is helping scientists model thousands of transcription factors and genes in the human genome, providing new information on these genes and how they work/change over time.

Illustrated liver shows points of light, connected by brightly colored lines. Signifies how researchers are using data and technology to better understand liver cancer.

Machine Learning Helps Boost Accuracy for Liver Cancer Screening

With the help of machine learning, NCI-funded researchers were able to boost the prognostic power of a common blood test for liver cancer.

Artist illustration of lungs set against a background of a stained pathology slide.

NCI-Funded Researchers Develop a New Model for Interpreting Pathology

Interpreting whole slide images can be a labor intensive and difficult task. A recent article describes a new approach that helps classify cancer and predict how it will progress.

Scan of the human body with AI logo

NCI Study Shows AI-Assisted Contouring Improves Prostate Cancer Treatment Efficacy

In the study, artificial intelligence (AI)-assisted contours outperformed manual contours, indicating the technology’s potential to enhance treatment strategies and improve outcomes for patients.

two people, one in a lab coat one in regular clothes, looking at a tablet. Data themed icons in background.

Predicting Cancer Treatment Responses with AI Tool PERCEPTION

Discover a new AI-driven tool that uses single-cell RNA data to help predict patient responses to cancer treatments.

3-D illustration of four cells, shown in blue with large red cell nuclei. Two cells are secreting small round bubbles from their surfaces. These bubbles represent exosomes, small cargo-carrying cell structures that have a part in diseases like cancer.

Seeking a Better Biopsy? NCI-Funded Researchers Are Using Machine Learning to Identify Exosome Biomarkers

NCI-funded researchers used machine learning to characterize a cancer biomarker based on exosomes. Their biomarker worked well using non-invasive sources, such as blood and urine, allowing the researchers to catch cancer early, even in tumors of undetermined origins.

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