Applying the Distributional Data Analysis Tool of Metabolism Index Density (MID), and Using Daily Metabolism Index (MI) Data from a Chronic Diseases Patients Past 6 Years Record to Investigate the Relationship Between his Overall Health Conditions and his Risk Probabilities of having a Stroke or Cardiovascular Disease Based on GHMethod: Math-Physical Medicine (No. 521)

Abstract

Gerald C Hsu

Recently, the author conducted a series of medical research projects by applying a distributional data density analysis tool on his weight, glucose, blood pressure (BP), and heart conditions, while using his collected big data regarding certain biomarker’s density distribution during certain selected years. In this article, he investigates his collected metabolism index density (MID%) within a time span of ~6 years (1/1/2016 - 9/13/2021) and its relationship with his risk probability of having a cardiovascular disease (CVD) or stroke within the same time period. With this data, he can interpret the results and explore additional and in-depth information since he is most familiar with his own health conditions. The findings from his own data is definitely applicable to other patients with chronic diseases. The main purpose of writing this series of research articles is to further demonstrate the applicability and power of the specific distributional data density analysis tool.

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