Public Health

Advancement of post-market surveillance of medical devices leveraging artificial intelligence: Infusion pumps case study.

BackgroundAnalysis of data from incident registries such as MAUDE has identified the need to improve surveillance and maintenance strategies for infusion pumps to enhance patient and healthcare staff safety.ObjectiveThe ultimate goal is to enhance infusion pump management strategies in healthcare facilities, thus transforming the current reactive approach to infusion pump management into a proacti...

Artificial intelligence-powered image analysis: A paradigm shift in infectious disease detection.

The global burden of infectious diseases significantly affects mortality rates, with their varying symptoms making it challenging to assess and determine the severity of infections. Different countries face unique challenges related to these diseases. This study introduces innovative Artificial Intelligence (AI) based methodologies to enhance diagnostic accuracy through the analysis of medical ima...

Machine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding.

BACKGROUND: The global outbreak of the coronavirus disease 2019 (COVID-19) has been enormously damaging, in which prolonged shedding of severe acute r...

Artificial intelligence meets the world experts; updates and novel therapies in autoimmunity - The 14th international congress on autoimmunity 2024 (AUTO14), Ljubljana.

The bi-annual international congress on autoimmunity is a huge opportunity for the medical community to discuss the latest updates in the field. Durin...

Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer.

Brain metastases (BMs) in extensive-stage small cell lung cancer (ES-SCLC) are often associated with poor survival rates and quality of life, making t...

Applications of artificial intelligence for chemical analysis and monitoring of pharmaceutical and personal care products in water and wastewater: A review.

Specifying and interpreting the occurrence of emerging pollutants is essential for assessing treatment processes and plants, conducting wastewater-bas...

Role of artificial intelligence in early diagnosis and treatment of infectious diseases.

Infectious diseases remain a global health challenge, necessitating innovative approaches for their early diagnosis and effective treatment. Artificia...

Machine learning algorithms for prediction of measles one vaccination dropout among 12-23 months children in Ethiopia.

INTRODUCTION: Despite the availability of a safe and effective measles vaccine in Ethiopia, the country has experienced recurrent and significant meas...

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

In recent years, public health events have significantly impacted various aspects of human production and daily life, particularly in the domains of d...

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

Tuberculosis (TB), the second leading infectious killer globally, claimed the lives of 1.3 million individuals in 2022, after COVID-19, surpassing the...

Recommendations for the Development of Artificial Intelligence Applications for the Retail Level.

Some of the early applications of artificial intelligence (AI) for food safety appear to be intended for use at the level of manufacturing and distrib...

LarvaeCountAI: a robust convolutional neural network-based tool for accurately counting the larvae of Culex annulirostris mosquitoes.

Accurate counting of mosquito larval populations is essential for maintaining optimal conditions and population control within rearing facilities, ass...

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

The COVID-19 outbreak caused saturations of hospitals, highlighting the importance of early patient triage to optimize resource prioritization. Herein...

MultiADE: A Multi-domain benchmark for Adverse Drug Event extraction.

OBJECTIVE: Active adverse event surveillance monitors Adverse Drug Events (ADE) from different data sources, such as electronic health records, medica...

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,...

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 Publi...

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...