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COVID-19

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Predictive risk models for COVID-19 patients using the multi-thresholding meta-algorithm.

Scientific reports
This study aims to develop a Machine Learning model to assess the risks faced by COVID-19 patients in a hospital setting, focusing specifically on predicting the complications leading to Intensive Care Unit (ICU) admission or mortality, which are min...

AI for Analyzing Mental Health Disorders Among Social Media Users: Quarter-Century Narrative Review of Progress and Challenges.

Journal of medical Internet research
BACKGROUND: Mental health disorders are currently the main contributor to poor quality of life and years lived with disability. Symptoms common to many mental health disorders lead to impairments or changes in the use of language, which are observabl...

Comparative analysis of volatility forecasting for healthcare stock indices amid public health crises: a study based on the Bayes-CNN model.

Frontiers in public health
In recent years, public health events have significantly impacted various aspects of human production and daily life, particularly in the domains of disease transmission and economic stability. While many scholars have primarily focused on the influe...

A comprehensive study on tuberculosis prediction models: Integrating machine learning into epidemiological analysis.

Journal of theoretical biology
Tuberculosis (TB), the second leading infectious killer globally, claimed the lives of 1.3 million individuals in 2022, after COVID-19, surpassing the toll of HIV and AIDS. With an estimated 10.6 million new TB cases worldwide in 2022, the gravity of...

The Promise of Remote Patient Monitoring.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
The promise of remote patient monitoring (RPM) lies in its ability to revolutionize health care delivery by enabling continuous, real-time tracking of patient health outside traditional clinical settings. The COVID-19 pandemic accelerated the adoptio...

Advantages of Metabolomics-Based Multivariate Machine Learning to Predict Disease Severity: Example of COVID.

International journal of molecular sciences
The COVID-19 outbreak caused saturations of hospitals, highlighting the importance of early patient triage to optimize resource prioritization. Herein, our objective was to test if high definition metabolomics, combined with ML, can improve prognosti...

Enhancing multiclass COVID-19 prediction with ESN-MDFS: Extreme smart network using mean dropout feature selection technique.

PloS one
Deep learning and artificial intelligence offer promising tools for improving the accuracy and efficiency of diagnosing various lung conditions using portable chest x-rays (CXRs). This study explores this potential by leveraging a large dataset conta...

Protein-Protein Interaction Networks Derived from Classical and Machine Learning-Based Natural Language Processing Tools.

Journal of proteome research
The study of protein-protein interactions (PPIs) provides insight into various biological mechanisms, including the binding of antibodies to antigens, enzymes to inhibitors or promoters, and receptors to ligands. Recent studies of PPIs have led to si...

Assessing COVID-19 Vaccine Effectiveness and Risk Factors for Severe Outcomes through Machine Learning Techniques: A Real-World Data Study in Andalusia, Spain.

Journal of epidemiology and global health
BACKGROUND: COVID-19 vaccination has become a pivotal global strategy in managing the pandemic. Despite COVID-19 no longer being classified as a Public Health Emergency of International Concern, the virus continues affecting people worldwide. This st...

Academic-related stressors predict depressive symptoms in graduate students: A machine learning study.

Behavioural brain research
BACKGROUND: Graduate students face higher depression rates worldwide, which were further exacerbated during the COVID-19 pandemic. This study employed a machine learning approach to predict depressive symptoms using academic-related stressors.