With the rapid advancement of information technology, online information has been
exponentially growing day by day, especially in the form of text documents such as news …

Human healthcare is one of the most important topics for society. It tries to find the correct
effective and robust disease detection as soon as possible to patients receipt the …

Background An appropriate sample size is essential for obtaining a precise and reliable
outcome of a study. In machine learning (ML), studies with inadequate samples suffer from …

Data collected from clinical trials and cohort studies, such as dementia studies, are often
high-dimensional, censored, heterogeneous and contain missing information, presenting …

In the era of big data, all types of data with increasing samples and high-dimensional
attributes are demonstrating their important roles in various fields, such as data mining …

Feature selection has been an important research area in data mining, which chooses a
subset of relevant features for use in the model building. This paper aims to provide an …

Over the past decades, there has been considerable interest in applying statistical machine
learning methods in survival analysis. Ensemble based approaches, especially random …

Purpose Surgical oncologists are frequently confronted with the question of expected long-
term prognosis. The aim of this study was to apply machine learning algorithms to optimize …

Background and objective Datamining (DM) has, over the last decade, received increased
attention in the medical domain and has been widely used to analyze medical datasets in …

In this study, we propose a novel approach called DCNN-ViT-GRU, which combines deep
Convolutional Neural Networks (CNNs) with Gated Recurrent Units (GRUs) and the Vision …