Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood.
Deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems, patient classification, fundamental biological processes, and treatment of patients and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges.
Predict the comprehensive chronic and preventive care needs of individual patients with unparalleled precision.
Predict and prioritize high-risk members and use Contributing Factors insights to personalize outreach and interventions.
Strengthen commercial success, gain precision insights into key cohorts, and power digital therapeutics and value-based contracts.