Type 2 diabetes mellitus (T2DM) often results in high morbidity and mortality. In addition, T2DM presents a substantial financial burden for individuals and their families, health systems, and societies. According to studies and reports, globally, …
In this paper, we demonstrate the development and validation of the 10-years type 2 diabetes mellitus (T2DM) risk prediction models based on large survey data. The Survey of Health, Ageing and Retirement in Europe (SHARE) data collected in 12 …
Machine Learning (ML) models are often complex and difficult to interpret due to their “black-box” characteristics. Interpretability of a ML model is usually defined as the degree to which a human can understand the cause of decisions reached by a ML …
There is a need of ensuring machine learning models that are interpretable. Higher interpretability of the model means easier comprehension and explanation of future predictions for end-users. Further, interpretable machine learning models allow …
Machine learning based predictive models have been used in different areas of everyday life for decades. However, with the recent availability of big data, new ways emerge on how to interpret the decisions of machine learning models. In addition to …