PECLIDES Neuro - A Personalisable Clinical Decision Support System for Neurological Diseases

Abstract

Neurodegenerative diseases such as Alzheimers and Parkinsons impact millions of people worldwide. Early diagnosis has proven to greatly increase the chances of slowing down the diseases progression. Correct diagnosis often relies on the analysis of large amounts of patient data, and thus lends itself well to support from machine learning algorithms, which are able to learn from past diagnosis and see clearly through the complex interactions of a patients symptoms. Unfortunately, many contemporary machine learning techniques fail to reveal details about how they reach their conclusions, a property considered fundamental when providing a diagnosis. This is one reason why we introduce our Personalisable Clinical Decision Support System PECLIDES that provides a clear insight into the decision making process on top of the diagnosis. Our algorithm enriches the fundamental work of Masheyekhi and Gras in data integration, personal medicine, usability, visualisation and interactivity.\n\nOur decision support system is an operation of translational medicine. It is based on random forests, is personalisable and allows a clear insight into the decision making process. A well-structured rule set is created and every rule of the decision making process can be observed by the user (physician). Furthermore, the user has an impact on the creation of the final rule set and the algorithm allows the comparison of different diseases as well as regional differences in the same disease1.