Using artificial intelligence to advance personalized medicine

Opened less than a year ago, the Swiss Data Science Center - a joint initiative between EPFL and ETH Zurich - has already launched eight research projects in fields ranging from personalized medicine and environmental protection to open science. Each project brings together experts from several disciplines to join forces in tackling some of society's biggest challenges. One of the eight research projects, involving personalized medicine, stands to revolutionize treatment options for cancer patients. It is being carried out by EPFL's Signal Processing Laboratory (LTS4) in association with Lausanne University Hospital (CHUV). The project scientists are using advanced machine-learning algorithms to analyze images of tumor cells and identify the distinguishing features of each type of tumor. That will enable doctors to better categorize patients' tumors and select the most effective treatment for each one, broadening the range of personalized therapies available. This type of information, which has not yet been widely exploited, will be obtained by automatically analyzing vast amounts of data. "Personalized medicine is a rapidly growing field, thanks largely to high-speed sequencing," says Olivier Michielin, chief physician of the analytic personalized oncology division at the CHUV. "Today, oncologists choose cancer treatments based in part on the shape of the tumor as seen under a microscope." And while shape can be useful for initially classifying a tumor, the information generated from sophisticated, interpretable algorithms - combined with human judgment - can allow for a much more granular diagnosis. Developing personalized treatments