This study focuses on investigating the performance of different machine learning algorithms
and corresponding comparative analysis in predicting cardiovascular disease. Globally this …

Data bias is a major concern in biomedical research, especially when evaluating large-scale
observational datasets. It leads to imprecise predictions and inconsistent estimates in …

Precision, Recall, and F1-score are metrics that are often used to evaluate model
performance. Precision and Recall are very important to consider when the data is …

K-Nearest Neighbour (KNN) a well-known method that is using in several real-life
applications that involve machine learning and data mining in the real world. It finds the …

Generation error is one of the shortcomings of the classical mean-variance portfolio
selection model which would result in unstable performance in out-of-sample data sets …

Storm surge has recently emerged as a major concern. In case it occurs, we suffer from the
damages it creates. To predict its occurrence, machine learning technology can be …

Cavendish banana is an important export product of many countries, while postharvest
banana classification also impacts plantation income. The quality inspection standard …

Today, closed-circuit television (CCTV) is widely used in various fields. If authorized by law,
CCTV can be used to identify drug users in public places or specific areas. It can estimate …

Abstract Systems biology is an endeavor to explore various interconnected biological
processes as a system toward discovery in medical applications, drug discovery …

Credit risk now is considered like the most important risk faced by banks and financial
institutions. For this reason, predictive analytics became the barometer of financiers with a …