Public Health

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

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 significant biological breakthroughs. For example, the study of PPIs involved in the human:SARS-CoV-2 viral infection mechanism aided in the development...

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

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 study aimed to evaluate risk factors and vaccine effectiveness on COVID-19-related hospital admissions, intensive care unit (ICU) admission and mortalit...

Impact of different nephrectomy types on M0 renal cell carcinoma outcomes in a propensity score matching and deep learning study.

There are few analyses comparing complete nephrectomy with resection of the renal parenchyma only (CN) or radical nephrectomy that includes simultaneo...

A multi-layer neural network approach for the stability analysis of the Hepatitis B model.

In the present study, we explore the dynamics of Hepatitis B virus infection, a significant global health issue, through a newly developed dynamics sy...

Crowdsourcing Adverse Events Associated With Monoclonal Antibodies Targeting Calcitonin Gene-Related Peptide Signaling for Migraine Prevention: Natural Language Processing Analysis of Social Media.

BACKGROUND: Clinical trials demonstrate the efficacy and tolerability of medications targeting calcitonin gene-related peptide (CGRP) signaling for mi...

Personalized cancer vaccine design using AI-powered technologies.

Immunotherapy has ushered in a new era of cancer treatment, yet cancer remains a leading cause of global mortality. Among various therapeutic strategi...

The Role of Artificial Intelligence in Accelerating Vaccine Development: Challenges and Opportunities in Pandemic Preparedness.

Artificial intelligence (AI) has been studied and applied to medicines and vaccine development. However, there is still a need to understand the proce...

Random survival forest algorithm for risk stratification and survival prediction in gastric neuroendocrine neoplasms.

This study aimed to construct and assess a machine-learning algorithm designed to forecast survival rates and risk stratification for patients with ga...

Enhancing SARS-CoV-2 Lineage Surveillance through the Integration of a Simple and Direct qPCR-Based Protocol Adaptation with Established Machine Learning Algorithms.

Emerging and evolving Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) lineages, adapted to changing epidemiological conditions, present u...

Artificial intelligence in predicting pathogenic microorganisms' antimicrobial resistance: challenges, progress, and prospects.

The issue of antimicrobial resistance (AMR) in pathogenic microorganisms has emerged as a global public health crisis, posing a significant threat to ...

The role of aspirin in preventing gastrointestinal cancers.

Cancer remains an increasing global health issue and is projected to cause 50% of all global deaths by 2050. Gastrointestinal (GI) tract cancers curre...

The power of artificial intelligence for managing pandemics: A primer for public health professionals.

Artificial intelligence (AI) applications are complex and rapidly evolving, and thus often poorly understood, but have potentially profound implicatio...

The role of artificial intelligence in the management of liver diseases.

Universal neonatal hepatitis B virus (HBV) vaccination and the advent of direct-acting antivirals (DAA) against hepatitis C virus (HCV) have reshaped ...

Vaccine development using artificial intelligence and machine learning: A review.

The COVID-19 pandemic has underscored the critical importance of effective vaccines, yet their development is a challenging and demanding process. It ...

Artificial intelligence-driven pharmaceutical industry: A paradigm shift in drug discovery, formulation development, manufacturing, quality control, and post-market surveillance.

The advent of artificial intelligence (AI) has catalyzed a profound transformation in the pharmaceutical industry, ushering in a paradigm shift across...

Machine Learning Early Detection of SARS-CoV-2 High-Risk Variants.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved many high-risk variants, resulting in repeated COVID-19 waves over the pa...

A deep drug prediction framework for viral infectious diseases using an optimizer-based ensemble of convolutional neural network: COVID-19 as a case study.

The SARS-CoV-2 outbreak highlights the persistent vulnerability of humanity to epidemics and emerging microbial threats, emphasizing the lack of time ...

FluPMT: Prediction of Predominant Strains of Influenza A Viruses via Multi-Task Learning.

Seasonal influenza vaccines play a crucial role in saving numerous lives annually. However, the constant evolution of the influenza A virus necessitat...

Estimating the prevalence of select non-communicable diseases in Saudi Arabia using a population-based sample: econometric analysis with natural language processing.

BACKGROUND: Non-communicable diseases (NCDs) are a major public health challenge globally, including in Saudi Arabia. However, measuring the true exte...

Precision Epidemiology: A Computational Analysis of the Impact of Algorithmic Prediction on the Relationship Between Population Epidemiology and Clinical Epidemiology.

OBJECTIVES: Precision Medicine (PM) uses advanced Machine Learning (ML) techniques and big data to develop personalized treatments, but healthcare sti...