The increasing access to health data worldwide is driving a resurgence in machine learning
research, including data-hungry deep learning algorithms. More computationally efficient …

Background: The lengthy and expensive process of developing a novel medicine often takes
many years and entails a significant financial burden due to its poor success rate …

Tradition K-means clustering algorithm is easy to fall into local optimum, poor clustering
effect on large capacity data and uneven distribution of clustering centroids. To solve these …

Public health initiatives must be made using evidence-based decision-making to have the
greatest impact. Machine learning algorithms are created to gather, store, process, and …

Summary Pummelo (Citrus maxima or Citrus grandis) is a basic species and an important
type for breeding in Citrus. Pummelo is used not only for fresh consumption but also for …

This paper explores the strategic planning required for a zero-carbon-emission AC/DC
microgrid, which integrates renewable energy sources and electric vehicles (EVs) within its …

Background and objective: Arrhythmia is a widely seen cardiologic ailment worldwide, and
is diagnosed using electrocardiogram (ECG) signals. The ECG signals can be translated …

Abstract Background and Objective While the development of artificial intelligence (AI)
technologies in medicine has been significant, their application to acute and chronic pain …

Objectives: Diabetic patients are often diagnosed with several comorbidities. The aim of the
present study was to investigate the relationship between different combinations of risk …

In the field of medical science, accurate prediction is a difficult and challenging task. But, the
presence of missing values and outliers can make the prediction task more complicated …