Infectious Disease

Assessing Readability, Understandability, and Actionability of ACPA Educational Resources and Utility of LLMs to Improve Accessibility for Caregivers.

ObjectiveIt is important for parents and caregivers of children with cleft lip and/or palate to easily understand educational resources provided by the American Cleft Palate-Craniofacial Association (ACPA). This study aimed to assess the readability, understandability, and actionability of ACPA resources, and the utility of large language models (LLMs) in their improvement.DesignACPA resources wer...

Microbiome-metabolome generated bile acids gatekeep infliximab efficacy in Crohn's disease by licensing M1 suppression and Treg dominance.

INTRODUCTION: Despite the effectiveness of infliximab in treating Crohn's disease (CD), up to 40 % of patients fail to respond adequately. OBJECTIVES: This study aimed to identify predictive biomarkers of primary non-response to infliximab in treatment-naïve CD patients by characterizing baseline gut microbiome-metabolome interactions and to validate their mechanistic role in driving therapeutic r...

How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach.

OBJECTIVES: To identify relevant objective variables for retrospective identification of 'suspected infection' and sepsis, using behavioural artificia...

AI-driven diagnosis of Lassa fever: Evidence from Nigerian clinical records.

BACKGROUND: Neglected Tropical Diseases (NTDs), particularly Lassa fever, remain a significant public health challenge in Nigeria, often presenting wi...

Cancer vaccines: Discovery, development, and challenges for clinical translation.

Cancer vaccines stimulate antitumor immunity by delivering tumor antigens and, in recent years, have emerged as a promising therapeutic strategy again...

QDCRNet: Quantum dilated convolutional recurrent network for virus detection using gene expression data.

Viral Infections cause several common human illnesses, like the common cold, flu, mouth blisters, and chickenpox. However, numerous viruses, including...

Algal/bacterial membrane bioreactor for bioremediation of hazardous landfill leachate containing 1,4-dioxane: An artificial neural network modeling.

This study developed an artificial neural network (ANN) model to predict the 1,4-dioxane removal efficiency from hazardous landfill leachate treated b...

Leveraging machine learning for predicting Opisthorchis viverrini infection in cats: A tool for veterinary epidemiology.

Opisthorchis viverrini (Ov) infection is a major public health concern in the Greater Mekong Subregion, with cats as key reservoir hosts. Although mac...

An update on experimental to large-scale production of bacteriophages against superbugs: a review.

The escalating problem of antibiotic resistance has sparked renewed interest in bacteriophages (phages) as potential substitutes for conventional anti...

Biomarkers associated with Hashimoto's thyroiditis induced by viral infection: An integrative bioinformatics and machine learning.

OBJECTIVE: Hashimoto's thyroiditis (HT) is a common disease characterized by autoimmune injury of the thyroid. Its pathogenesis entails complex intera...

Predicting delirium in critically Ill COVID-19 patients using EEG-derived data: a machine learning approach.

Delirium is a severe and common complication among critically ill patients, particularly those with SARS-CoV-2 infection, contributing to increased mo...

EuroSCORE II: Current limitations and physiological gaps in risk stratification.

Risk stratification remains critical in cardiac surgery, enabling clinicians to predict adverse outcomes and guide perioperative management. The Europ...

Search for Specific Inhibitors Targeting Type IA Topoisomerases.

The type IA topoisomerase subfamily includes bacterial topoisomerase I and topoisomerase III encoded by topA and topB genes, reverse gyrase found in t...

Crafting an innovative one health-aligned machine learning framework for neglected tropical diseases elimination.

INTRODUCTION: Strategic investment in new interventions is crucial for controlling and eliminating NTDs. However, selecting the optimal intervention c...

Evaluating predictive performance and generalizability of traditional and artificial intelligence models in predicting surgical site infections postspinal surgery: a systematic review.

BACKGROUND CONTEXT: Surgical site infections (SSIs) are a significant complication following spinal surgery. These infections contribute to increased ...

A Machine Learning Approach to Microcalorimetric Pattern Classification of Pathogens in Synovial Fluid.

Isothermal microcalorimetry (IMC) is a promising tool for diagnosing periprosthetic joint infection (PJI), based on real-time measurement of growth-re...

Computational exploration of global venoms for antimicrobial discovery with Venomics artificial intelligence.

The rise of antibiotic-resistant pathogens, particularly gram-negative bacteria, highlights the urgent need for novel therapeutics. Drug-resistant inf...

Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis.

BACKGROUND: Mycobacterium tuberculosis (MTB) is a human-specific pathogen that primarily infects humans, causing tuberculosis (TB). Antimicrobial resi...

Identification of diagnostic biomarkers and dissecting immune microenvironment with crosstalk genes in the POAG and COVID-19 nexus.

An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesized, but the causal link and shared mechanisms rem...

Machine learning-selected minimal features drive high-accuracy rule-based antibiotic susceptibility predictions for via metagenomic sequencing.

Antimicrobial resistance (AMR) represents a critical global health challenge, demanding rapid and accurate antimicrobial susceptibility testing (AST) ...