Deep learning technology can be very strong at identifying complex patterns within large data sets and mapping them to simple classifications like diagnosing a certain disease, or whether a disease will progress, and how soon. This information is incredibly useful in the process of clinical trials and drug development, where the end goals are to test and discover if treatment is working and how well.

Using deep learning tech in clinical trials is the ideal application to speed up drug development and get more effective drugs to the clinic faster, ultimately impacting patients positively. To understand medical treatments effectively, especially for conditions like lung and heart disease, there are often large and complex data sets that need rigorous processing, a hard task for any clinician or even team clinicians to undertake.

With current developments in AI, we now can spot patterns, link disease outcomes, and analyse images at super-speed across hundreds and thousands of data points. Not only this, but deep learning has the potential to improve clinical trial workflow and processes and improve outcomes of drug discovery.