Bringing machine learning closer to non-experts: proposal of a user-friendly machine learning tool in the healthcare domain

Applying Machine Learning to solve or support complex tasks is growing in popularity in a lot of different contexts. One of these contexts is the medical domain. Through Machine Learning, specific problems such as diagnosis, classification, disease detection, segmentation, assessment of organ functions, etc., can be eased by assisting physicians with useful models and their outcomes. However, understanding the application of Machine Learning and Artificial Intelligence algorithms requires expert knowledge and significant data science skills. This work presents a proposal for a user-friendly Machine Learning tool, focusing on providing a good user experience for physicians as well as an educative context for understanding the tasks involved in Machine Learning pipelines, their configuration, and their outputs.