The Mark Foundation for Cancer Research (MFCR) has contributed funding to eight different research projects that involve AI. Overall, the funding totaled $2.2 million.
A majority of the chosen projects began in April 2019 at a workshop hosted by both MFCR and Carnegie Mellon University. The workshop promoted studying advanced technologies by collaborating with other researchers.
“Bringing together scientists from varying disciplines is critical to tackling the toughest challenges in cancer research,” Ryan Schoenfeld, PhD, MFCR’s vice president for scientific research, said in a prepared statement. “We’re glad to see promising collaborations emerge from our workshop and to be the first foundation with such a robust portfolio at the intersection of AI and cancer research. We’re just at the beginning stage of harnessing the incredible power of machine learning in the fight against cancer, and we’re excited to see where these projects take us.”
The eight projects receiving funding are:
- “Using Smartphones and Wearables for Early Detection of Central Nervous System Tumors”
- “Using Blood Biomarkers to Aid App-Based Cancer Monitoring”
- “Using Artificial Intelligence to Predict Interactions between Immune and Tumor Cells”
- “Artificial Intelligence Assisted MRI Screening for Pediatric Cancers”
- “Detailed, Automated 3D Imaging of Pancreatic Cancers and Precancers”
- “Detecting Novel Cancer Mutations That Change the Genome’s 3D Structure”
- “New Imaging Methods for Identifying Structural Differences in Cancer Cells”
- “Advanced DNA Sequencing for Uncovering Novel Inheritable Carcinogenic Mutations”
Michael Schatz, PhD, of Johns Hopkins University and Eliezer Van Allen, MD, of the Dana-Farber Cancer Institute are collaborating on one of the projects receiving MFCR funding, “Advanced DNA Sequencing for Uncovering Novel Inheritable Carcinogenic Mutations.”
“We are incredibly grateful to The Mark Foundation for supporting this research and promoting our new collaboration,” Schatz said in the prepared statement. “The new technologies will let us examine these families with unprecedented resolution, and we expect to find tens of thousands of variants per patient that have never been observed before. Together, we will evaluate this new class of cancer risk variants and aim to improve cancer prevention, improve cancer therapy, and ultimately save lives.”
Michael has more than 16 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.