Identifying bacterial strains is essential in microbiology for various practical applications, such as disease diagnosis and quality monitoring of food and water. Classical machine learning algorithms have been utilized to identify bacteria based on ...
SIGNIFICANCE: Treatment planning for light-based therapies including photodynamic therapy requires tissue optical property knowledge. This is recoverable with spatially resolved diffuse reflectance spectroscopy (DRS) but requires precise source-detec...
UNLABELLED: is to train and test an ensemble of machine learning models, as well as to compare its performance with the BERT language model pre-trained on medical data to perform simple binary classification, i.e., determine the presence/absence of ...
Identifying forest types is vital for evaluating the ecological, economic, and social benefits provided by forests, and for protecting, managing, and sustaining them. Although traditionally based on expert observation, recent developments have increa...
This study aims to predict the significant duration (D5-75, D5-95) of seismic motion by employing machine learning algorithms. Based on three parameters (moment magnitude, fault distance, and average shear wave velocity), two additional parameters(fa...
INTRODUCTION: The aim of the work was to establish a prediction model of mild cognitive impairment (MCI) progression based on intestinal flora by machine learning method.
PURPOSE: Automated machine learning (AutoML) allows clinicians without coding experience to build their own deep learning (DL) models. This study assesses the performance of AutoML in detecting and localizing ocular toxoplasmosis (OT) lesions in fund...
Stress and health : journal of the International Society for the Investigation of Stress
Feb 27, 2024
We propose a novel approach for predicting stress severity by measuring sleep phasic heart rate variability (HRV) using a smart device. This device can potentially be applied for stress self-screening in large populations. Using a Holter electrocardi...
The use of artificial intelligence systems in clinical routine is still hampered by the necessity of a medical device certification and/or by the difficulty of implementing these systems in a clinic's quality management system. In this context, the k...
PURPOSE OF REVIEW: Artificial intelligence (AI) is quickly demonstrating the ability to address problems and challenges in the care of IBD. This review with commentary will highlight today's advancements in AI applications for IBD in image analysis, ...
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