We’re all familiar with those algorithms on our favorite e-commerce and streaming services that recommend purchases, books or movies based on what “others like you” have enjoyed.
In the industry, they are known as “recommender engines.”
Medical doctor Jonathan Chen is an assistant professor of medicine at Stanford and an expert in bioinformatics who wondered if the medical profession might benefit from similar artificial intelligence. He now creates recommender engines for doctors that comb real-world clinical data to help them make key decisions based on steps other doctors have taken with similar patients, empowering individuals with the collective experience of the many.
Chen tells Stanford Engineering’s The Future of Everything podcast that such programs will soon be commonplace in exam rooms, helping doctors become better at what they already do and making medical practice a more consistent, universal experience for everyone.