BackgroundThe idea that people will lose their jobs because of robots with artificial intelligence is one of the biggest recent concerns about artificial intelligence technology. There are predictions that unemployment will increase with the introduc...
Rural road accidents involving motorcycle riders present a formidable challenge to road safety globally. This study offers a comprehensive gender-based comparative analysis of rural road accidents among motorcycle riders, aimed at illuminating factor...
AIM/INTRODUCTION: We assess the efficacy of artificial intelligence (AI)-based, fully automated, volumetric body composition metrics in predicting the risk of diabetes.
Immunopharmacology and immunotoxicology
Nov 22, 2024
BACKGROUND: Immune checkpoint inhibitors (ICIs) show promise in cancer treatment but can lead to immune-related adverse events (irAEs), notably affecting the skin. Understanding the factors behind these skin reactions is crucial for effective managem...
In this paper, the first e-nose system coupled with machine learning algorithm for noninvasive measurement of total cholesterol level based on exhaled air sample was proposed. The study was conducted with the participation of 151 people, from whom a ...
BACKGROUND: The global outbreak of the coronavirus disease 2019 (COVID-19) has been enormously damaging, in which prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously 2019-nCoV) infection is a challenge in the...
Body composition assessment is very useful for evaluating a patient's status in the clinic, but recognizing, labeling, and calculating the body compositions would be burdensome. This study aims to develop a web-based service that could automate calcu...
BACKGROUND: Given the complexity and diversity of lichenoid vulvar disease (LVD) risk factors, it is crucial to actively explore these factors and construct personalized warning models using relevant clinical variables to assess disease risk in patie...
BACKGROUND: Atrial fibrillation (AF) is a progressive disease, and its clinical type is classified according to the AF duration: paroxysmal AF, persistent AF (PeAF; AF duration of less than 1 year), and long-standing persistent AF (AF duration of mor...
BACKGROUND: Accurate hospital length of stay (LoS) prediction enables efficient resource management. Conventional LoS prediction models with limited covariates and nonstandardized data have limited reproducibility when applied to the general populati...
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