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Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction.

This study explored the application of machine learning in predicting post-treatment outcomes for ch...

Assessment of image quality and impact of deep learning-based software in non-contrast head CT scans.

In this retrospective study, we aimed to assess the objective and subjective image quality of differ...

Oral ketamine effects on dynamics of functional network connectivity in patients treated for chronic suicidality.

The underlying brain mechanisms of ketamine in treating chronic suicidality and the characteristics ...

Optimizing recombinant antibody fragment production: A comparison of artificial intelligence and statistical modeling.

Maximizing the recombinant protein yield necessitates optimizing the production medium. This can be ...

A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability.

The post-effects of the COronaVIrus Disease (COVID-19) vary depending on socioeconomic and biologica...

Random forest models of food safety behavior during the COVID-19 pandemic.

Machine learning approaches are increasingly being adopted as data analysis tools in scientific beha...

Employing machine learning for enhanced abdominal fat prediction in cavitation post-treatment.

This study investigates the application of cavitation in non-invasive abdominal fat reduction and bo...

The value of linear and non-linear quantitative EEG analysis in paediatric epilepsy surgery: a machine learning approach.

Epilepsy surgery is effective for patients with medication-resistant seizures, however 20-40% of the...

Predicting osteoporotic fractures post-vertebroplasty: a machine learning approach with a web-based calculator.

PURPOSE: The aim of this study was to develop and validate a machine learning (ML) model for predict...

Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle.

This study aimed to compare the accuracy of IFN-Ï„ stimulated gene abundance (ISGs) in peripheral blo...

Explaining deep learning for ECG analysis: Building blocks for auditing and knowledge discovery.

Deep neural networks have become increasingly popular for analyzing ECG data because of their abilit...

A Pilot, Predictive Surveillance Model in Pharmacovigilance Using Machine Learning Approaches.

INTRODUCTION: The identification of a new adverse event (AE) caused by a drug product is one of the ...

Machine learning for predicting elective fertility preservation outcomes.

This retrospective study applied machine-learning models to predict treatment outcomes of women unde...

A Test Statistic Estimation-Based Approach for Establishing Self-Interpretable CNN-Based Binary Classifiers.

Interpretability is highly desired for deep neural network-based classifiers, especially when addres...

Exploring post-COVID-19 health effects and features with advanced machine learning techniques.

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a rang...

Protocol to identify biomarkers in patients with post-COVID condition using multi-omics and machine learning analysis of human plasma.

Here, we present a workflow for analyzing multi-omics data of plasma samples in patients with post-C...

Detecting white spot lesions on post-orthodontic oral photographs using deep learning based on the YOLOv5x algorithm: a pilot study.

BACKGROUND: Deep learning model trained on a large image dataset, can be used to detect and discrimi...

The gut microbiome associates with phenotypic manifestations of post-acute COVID-19 syndrome.

The mechanisms underlying the many phenotypic manifestations of post-acute COVID-19 syndrome (PACS) ...

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