JADBio: What is AutoML, and how can it be applied in Life Sciences?

Automated machine learning (AutoML) refers to creating a process of applying machine learning to real-world problems, automating the time-consuming and iterative tasks of model development, and accelerating time to knowledge discovery. The primary goal behind the use of AutoML is to achieve a degree of automation in processes that would allow anyone to apply machine learning models and techniques even if they do not have any expertise in machine learning or coding. That does not mean it can’t be used by an experienced data scientist; AutoML can make it easier and faster for them to do their work, enabling them to accurately scale their efforts while focusing on what matters, knowledge discovery. This last caveat is important when it comes to life scientists. For example, an oncologist working with gene data and cancer samples needs to know which biomarkers collectively lead to optimal predictions, and understand their role in the analysis and predictive outcome.