Bio-IT World April 14, 2021
In a perfect, patient-centric world, anyone diagnosed with cancer would know the cause—including the DNA-damaging environmental exposures, health habits, and inherited factors—based on the unique mutational pattern of their tumor, says Cristian Tomasetti, Ph.D., associate professor of oncology at Johns Hopkins Medicine with a joint appointment in biostatistics in the university’s school of public health. This will be an important job for machine learning in the future, even if “the answer will sometimes be the normal process of aging, what I call bad luck.”
Tomasetti and his colleagues at the Johns Hopkins Kimmel Cancer Center are off to a good start with their newly developed supervised machine learning algorithm that does the best job yet of connecting tissue-specific cancers to...