Analyzing Disease Data Through Machine Learning
In recent years, significant advances have been made in Artificial Intelligence (AI) and machine learning such that they have become valuable tools when analyzing large amounts of data. In complex diseases where the relationships between multiple biomarkers and other clinical factors is important, it becomes crucial to understand these relationships so as to create reliable diagnostics that not only benefit the patient but the physician as well.
In complex diseases such non-alcoholic fatty liver disease (NAFLD) it is imperative to understand these relationships to determine reliable diagnostics and develop predictive models so that patient and physician not only are told if the disease is present, but also are told what are the chances that the patient will develop the aggressive form of the disease later. This information when provided early can allow the patient to be treated with available medications as well as allow the patient to make any lifestyle changes, thus saving their life as well as saving millions of dollars in costly surgical procedures such as liver resection or complete liver transplant.
Arrow Dx working with its academic collaborators as well as its hospital and physician collaborators is working to develop proprietary algorithms to analyze disease data so that it can improve its diagnostic platform. We aim to provide a software package that will help physicians, researchers, hospitals, and clinics analyze complex diagnostic data. Our ultimate aim is to provide patients and physicians with the most accurate diagnostic data in real time such that patient lives can be saved as well reduce the cost of expensive surgical procedures.