How to estimate the age of your brain with MRI data
Abstract
Healthcare is an industry that raises the highest hopes regarding the potential benefits of Artificial Intelligence (AI). Physicians and medical researchers will not become programmers or data scientists overnight, nor will they be replaced by them, but they will need an understanding of what AI actually is and how it works. Similarly, data scientists will need to collaborate closely with doctors to focus on relevant medical questions and understand patients behind the data.
This case study aims to connect both audiences (physicians/medical personnel and data scientists) by providing insights into how to apply machine learning to a specific medical use case. We will walk you through the reasoning of our approach and will enable you to accompany us on a practical journey (via our Colab notebook) focused on understanding the underlying mechanics of an applied machine learning model.
Our experiment focuses on creating and comparing algorithms of increasing complexity in a successful attempt to estimate the physiological age of a brain based on Magnetic Resonance Imaging (MRI) data. Based on this experiment we propose how this imaging biomarker could have an impact on the understanding of neurodegenerative diseases such as Alzheimer’s.
