A mobile app may soon be able to diagnose you with chronic health conditions using the sound of your voice. Scientists are building an artificial intelligence that analyzes vibrations in speech and breathing patterns to look for clues for illness. The National Institutes of Health is funding a mammoth research project to collect voice data that will build the AI. Experts already know that speech is altered by conditions like Parkinson's or stroke, while breathing is affected by lung diseases. But the hope is that the computer program will be able to diagnose a wide range of conditions - including cancer and depression.

Yael Bensoussan, MD, is part of the USF Health's department of Otolaryngology - Head & Neck Surgery. She's leading an effort to collect voice data that can be used to diagnose illnesses. Yael Bensoussan, MD, is part of the USF Health's department of Otolaryngology - Head & Neck Surgery. She's leading an effort to collect voice data that can be used to diagnose illnesses. Voices offer lots of information.

We survey in this article the connections between Machine Learning and Control Theory. Control Theory provide useful concepts and tools for Machine Learning. Conversely Machine Learning can be used to solve large control problems. In the first part of the paper, we develop the connections between reinforcement learning and Markov Decision Processes, which are discrete time control problems. In the second part, we review the concept of supervised learning and the relation with static optimization. Deep learning which extends supervised learning, can be viewed as a control problem. In the third part, we present the links between stochastic gradient descent and mean-field theory. Conversely, in the fourth and fifth parts, we review machine learning approaches to stochastic control problems, and focus on the deterministic case, to explain, more easily, the numerical algorithms.