Deep learning algorithms have recently achieved transformative results in machine perception tasks such as image and voice recognition, but can they improve patient lives by being used for disease recognition? Properly diagnosing disease has typically been limited by human accuracy, report turn-around time, geographic and economic barriers, population-level generalizations and an explosion of digital information at the point of diagnosis. Enlitic’s mission is to assist doctors in making personalized diagnoses by giving them the right data-centered tools. Deep learning can automatically discover clinically-relevant features by first architecting a hierarchy of patterns (loosely modelled on the brain’s own neural networks) and then rapidly updating those patterns upon observing examples. Enlitic is developing a deep neural network of the entire human body that will offer a new way forward for doctors to gain immediate access to the most relevant clinical information across early forms of disease. Enlitic’s vision is to understand and build a network that captures not only emergent points of disease but identifies the interrelated anatomic, metabolic and genomic correlates that give rise to both, disease and health.