Word2Vec for medical fraud detection

While most medical professionals adhere to strict standards in their capacity, medical fraud exists especially in today’s digital world. Data scientists and analysts have developed data science models and analysis techniques to detect medical fraud. All types of medical services have been codified together with text descriptions. These medical service codes have become important for data analytic purposes. However, the vast amount of medical codes, many of them being related, can be challenging for researchers. In this example, you will see that Word2Vec can be used to find the semantic relationships between codes. It helps you to group medical codes or to create features for your machine learning models. After reading this use case, you may be inspired by their approach to tackling a large coding system so you can use a similar approach in the medical field, or any other field.

Background

Medical abuse happens when any practice is...