Reinforcement learning (a sub-set of deep learning), has exciting scope for application health. Due to it’s ability to automatically determine ideal behaviour within a specific context, it can lead to more tailored and accurate treatments at reduced costs. In other words, more personalised and affordable medicine.
The machine learning technique has been found for example, to have superior capabilities in generating chemical compounds with desired physical, chemical, and/or bioactivity properties, leading to quicker drug development with lower side effects. This is a huge development for anyone who has had to endure drug after drug, and side-effect after side-effect, before finding the treatment right for them.
Researchers have also found potential for the use of reinforcement learning in:
- Medical image screening for diagnosis detection
- Medical chatbots
- Clinical decision making simulation
As with most of deep learning however, what’s been done so far is only scratching the surface and we can’t wait to see what new applications arise in the coming years.