Infectious Disease

AI-Enhanced Point-of-Care Diagnostics for Infectious Diseases in Resource-Limited Settings: A Scoping Review.

OBJECTIVES: To systematically map the extent and nature of research on AI-enhanced point-of-care (POC) and rapid diagnostic technologies for infectious diseases in resource-limited settings, and to identify gaps in disease coverage, geographic representation and validation rigour. METHODS: This scoping review followed JBI methodology and PRISMA-ScR guidelines. The protocol was registered on OSF (h...

Benchmarking large language models for cell-free RNA diagnostic biomarker discovery.

Large language models can synthesize biomedical knowledge, parse vast amounts of data, and generate code, positioning them as promising tools for biomarker discovery from high-throughput omics data. Here, we benchmark six models from OpenAI, Anthropic, and Google on plasma cell-free RNA datasets spanning three clinical cohorts: Kawasaki disease versus multisystem inflammatory syndrome in children,...

Physician adoption patterns of AI-driven clinical decision support systems in urinary tract infection management.

In 2021, Maccabi Healthcare Services (MHS) introduced "UTI Smart-Set" (UTIS), an AI-driven decision support system (DSS) based on a machine-learning (...

HIV-1 protease cleavage sites detection with a quantum convolutional neural network algorithm.

Human immunodeficiency virus type 1 (HIV-1) protease plays a crucial role in viral maturation by cleaving both viral and host precursor proteins. Accu...

TriNet-MoE: One New Neural Network Framework Based on Mixture of Experts for CXR-Based COVID-19 Detection.

As a low-dose portable imaging technology, chest X-ray (CXR) is widely used for the screening of lung diseases, including COVID-19. However, existing ...

Prevention is all you need: generative artificial intelligence for infection prevention and healthcare epidemiology.

PURPOSE OF REVIEW: Generative artificial intelligence, particularly large language models, has emerged as a promising tool for processing the vast amo...

Explainable deep learning techniques for microscopic fungi classification using a learnable threshold-based ReLULeaky activation function and transfer learning.

Fungal infections are an increasing risk to human health. They can pose a threat to life and cause a variety of health problems. The traditional diagn...

Gut fungal signatures in colorectal cancer and their potential for supporting diagnosis: a multi-cohort metagenomic analysis.

BACKGROUND: Colorectal cancer (CRC) is influenced by host factors and environmental exposures that shape gut microbial ecosystems. Although bacterial ...

Targeting emerging respiratory pathogens with Clamp Peptides: broad-spectrum inhibition of viral entry in 3D human lung models.

Rapid urbanization, migration and climate change are accelerating the appearance and diversification of respiratory viruses, overwhelming the pace at ...

Use of SNOMED CT, 2020-2025: literature review.

OBJECTIVE: To examine the evolving role and application of SNOMED CT (SCT) during 2020-2025, a period marked by the COVID-19 pandemic and accelerated ...

Machine learning-based prediction of early invasive mechanical ventilation in ICU patients with pneumonia: Development and external validation.

BACKGROUND: Pneumonia is a common critical illness in the intensive care unit (ICU), and a subset of patients rapidly progresses to respiratory failur...

Pre-implementation safety evaluation of an AI decision-support system for surgical antimicrobial prophylaxis.

BACKGROUND: Large language models (LLMs) show potential to support antimicrobial prescribing but require simulation-based, institution-specific safety...

From Correlation to Causality: Identifying Potential Environmental Drivers of Pathogenic Antibiotic-Resistant Bacteria in River Water Using Causal Machine Learning.

Pathogenic antibiotic-resistant bacteria (PARB) pose a serious public health threat within the One Health framework, yet identifying their potential e...

Classification of bacterial images obtained optically using some pre-trained models.

Rapid and accurate detection of water-borne bacteria is critical for safeguarding public health and preventing the spread of infections. Conventional ...

Association between the PaO2/FiO2-to-PaCO2 ratio and mortality in patients with sepsis: a retrospective study with dual-cohort validation.

BACKGROUND: Sepsis patients face a high mortality risk. Available prognostic biomarkers have certain limitations. This study explored the prognostic u...

Benchmarking deep learning architectures for MALDI-TOF mass spectrometry in infectious disease diagnostics and vector-borne disease surveillance.

Emerging global health threats, from antimicrobial resistance to vector-borne diseases, require scalable diagnostic solutions. Matrix-assisted laser d...

Artificial intelligence-enabled histological analysis in pre-clinical respiratory disease models: a scoping review.

Histological analysis is a cornerstone of pre-clinical respiratory disease research. It enables assessment of pathology, therapeutic effects, and mech...

Geospatial variation and machine learning approaches to predict open defecation practice in Zambia.

BACKGROUND: Open defecation is the disposal of human feces in fields, bushes, forests, open waterways, beaches, and other open areas. It worsens the e...

Explainable artificial intelligence to assess hospital financial performance during the COVID-19 pandemic through operating margin metric.

PURPOSE: This study addresses critical gaps in understanding hospital financial resilience during the COVID-19 pandemic by developing an AI framework ...

An antibiotic chatbot: Evaluation of a retrieval-augmented generation approach for providing guideline-based antimicrobial advice.

BACKGROUND: Large language models (LLMs) have potential to provide clinical infection advice, but variations in prevalent pathogens and antimicrobial ...