Reinforcement learning for healthcare
Reinforcement learning is a branch of artificial intelligence that provides methods to optimize sequential decisions for long-term outcomes. It has many potential applications in healthcare, such as improving treatment strategies, enhancing patient safety, and reducing costs.
- Contextual Bayesian non-stationary treatment recommendations
- Data safe havens, federated learning and other privacy-enhancing techniques
- Improving human board game performance through reinforcement learning
- Reinforcement learning for complex adaptive individual health interventions
- Simulation of patient data for micro-randomized trials
- Shrestha, S, Jain, S. A Bayesian-bandit adaptive design for N-of-1 clinical trials. Statistics in Medicine. 2021; 40: 1825– 1844. https://doi.org/10.1002/sim.8873