In a proof-of-concept study, an international scientific team led by Johns Hopkins Kimmel Cancer Center researchers has shown that a laboratory test using artificial intelligence tools has the potential to more accurately sort out which people with pancreatic cysts will go on to develop pancreatic cancers. The test, dubbed CompCyst (for comprehensive cyst analysis), incorporates measures of […]
Throughout his career, Donald Geman, ICM core faculty member and professor in the Department of Applied Mathematics and Statistics, has developed statistical methods for a variety of research applications. Geman’s most recent research published in the journal Proceedings of the National Academy of Sciences focuses on engineering an algorithm that may assist in differentiating between certain […]
Driver genes in different metastases from the same patient are remarkably similar, providing optimism for the success of future targeted therapies, according to a published study by Science. The report, “Minimal Functional Driver Gene Heterogeneity Among Untreated Metastases,” looked at data from samples that have spread from the site of origin to another part of the body in […]
Mathematicians and cancer scientists have found a way to simplify complex biomolecular data about tumors, in principle making it easier to prescribe the appropriate treatment for a specific patient. The digital approach from scientists at the Johns Hopkins University—a computational strategy transforms highly complex information into a simplified format that emphasizes patient-to-patient variation in the […]
Collin J. Tokheim, a doctoral student in the lab of ICM core faculty member Rachel Karchin, is the lead author of a paper titled, “Evaluating the evaluation of cancer driver genes,” which was published December 13, 2016 in the Early Edition of Proceedings of the National Academy of Sciences. Rachel Karchin, Associate Professor of Biomedical Engineering and William […]
