AI-based Data Preparation and Data Analytics in Healthcare: The Case of Diabetes
This work addresses the problem of improving diagnostic and therapeutic support for diabetologists through data analytics, but it appears incremental as it applies existing methods to a new healthcare dataset.
The paper tackled the challenge of applying AI and ML techniques to conceptualize, clean, and analyze a large diabetic patient dataset (the AMD database) to provide predictive insights for diabetologists, with initial results presented as part of an ongoing project.
The Associazione Medici Diabetologi (AMD) collects and manages one of the largest worldwide-available collections of diabetic patient records, also known as the AMD database. This paper presents the initial results of an ongoing project whose focus is the application of Artificial Intelligence and Machine Learning techniques for conceptualizing, cleaning, and analyzing such an important and valuable dataset, with the goal of providing predictive insights to better support diabetologists in their diagnostic and therapeutic choices.