There’s a lot of talk around the recent rise of machine learning (ML) and the promise it holds for oncology. Machine learning is quickly becoming a vital component of every-day medical testing, almost like a regular blood test, an MRI, or the old-fashioned stethoscope. ML assists healthcare providers, physicians, nurses, imaging technicians, and others in improving patient diagnosis in areas previously deemed as undiagnosable “dead-zones.”
Machine learning represents the most successful branch of artificial intelligence–development of programs with the capacity to learn from data, playing a prominent role in facilitating novel applications that rely on the identification, correlation, and classification of complex data patterns for patient stratification.
