Infectious Disease

Hybrid deep learning-based rapid broad-Spectrum antimicrobial susceptibility prediction from whole-genome assemblies.

Antimicrobial resistance (AMR) is a global public health threat. Mortality and poor treatment outcomes are the key consequences of AMR. Conventional antimicrobial susceptibility testing (AST) is slow, limited in coverage, and dependent on laboratory infrastructure, creating delays in clinical decision-making. In this study, we developed a hybrid deep learning model for broad-spectrum antimicrobial...

CellVision: A Deep Learning based Image Analysis Platform to Accelerate Immuno-Plaque Assay Data Processing for Dengue Vaccine Development.

Accurately detecting patterns of interest across a large number of images presents a significant challenge in data analysis for high-throughput analytical assays. In many cases, manual image review to some degree is necessary, deviating from a fully automated workflow desired in high-throughput platforms. CellVision, a deep learning-based workflow, was created using recent developments in AI-power...

Post-Pandemic Forecasting of Pediatric Acute Respiratory Infections with Deep Learning: A Multi-Pathogen, Multi-Time-Horizon Study.

BACKGROUND: Acute respiratory infections (ARIs) remain a major cause of morbidity and hospitalization in children worldwide. In the post-COVID-19 era,...

Based on a radiomics-clinical nomogram to predict the therapeutic effect of pulmonary cryptococcosis pneumonia.

We aimed to develop a radiomics-clinical nomogram to predict the therapeutic effect of PC pneumonia. A total of 255 PC pneumonia patients (165 cases w...

Explainable machine learning reveals evolutionary signals in influenza haemagglutinin.

Identifying amino acid changes that lead to phenotypic change is critical to viral surveillance. Common metrics, such as site-wise evolutionary rates ...

Combining machine learning and iterative experiments to keep pace with emerging viral variants of concern.

Modeling and predicting viral mutations before they emerge plays a crucial role in pandemic preparedness, enabling the early identification of emergin...

LXNet: A lightweight CNN for lung disease classification from Chest X-ray with XAI-based interpretability.

The diagnosis of lung diseases such as pneumonia and tuberculosis remains a major global health challenge, especially in resource-limited regions. Art...

Machine learning model based on clinical and imaging features for predicting fungal infections in children with leukemia.

BACKGROUND: Due to immunosuppression, mucosal barrier injury, and prolonged neutropenia resulting from both the disease and chemotherapy, along with t...

An Integrated Rotation-Programmed and Gravity-Driven Microfluidic Platform for Direct Bacterial Detection from Whole Blood.

For the precise molecular detection of bloodstream infection, sample processing is critical, as it involves purifying pathogenic DNA to circumvent the...

Predicting oxygen levels in microbial habitats using a metagenome-based approach.

Oxygen is a primary driver of the distribution and activity of microbial life. Since oxygen levels are often difficult to measure in situ, one potenti...

High performance deep-learning model for the diagnosis of auto-immune hepatitis based on histological whole slide images.

Autoimmune Hepatitis (AIH) is a liver disease with a wide clinical spectrum, driven by an abnormal immune response against the liver parenchyma. Chall...

Helicobacter pylori phages: resource landscape, translational challenges, and engineered antibacterial strategies.

Helicobacter pylori (H. pylori) is a globally prevalent gastric pathogen whose increasing antimicrobial resistance has reduced the efficacy of convent...

Geospatial and machine learning approaches for malaria risk mapping in flood-prone districts: Implications for public health decision-making.

OBJECTIVES: Malaria remains a major public health concern in flood-prone districts where environmental vulnerability and weak health infrastructure ex...

Hypericum perforatum L.: a legacy of herbal medicine in light of modern scientific evidence.

ETHNOPHARMACOLOGICAL RELEVANCE: Hypericum perforatum L. has been used for centuries in traditional medicine, with core therapeutic applications includ...

Enhancing the Efficacy of Ulcerative Colitis Treatment by Inhibiting LCN2-Mediated Pyroptosis Through Traditional Processing Techniques: With the rhizome of Atractylodes macrocephala Koidz. as an Example.

ETHNOPHARMACOLOGICAL RELEVANCE: Atractylodes Macrocephala Rhizome (AMR), the dried rhizome of Atractylodes macrocephala Koidz (family Asteraceae), is ...

Local infection signs at the catheter-insertion site: a large prospective multicentric cohort study.

OBJECTIVES: To describe the epidemiology of local signs at intravascular catheter insertion sites across catheter types and care settings, to compare ...

Global performance of predictive models for dengue severity, hospitalization and mortality: a systematic review and meta-analysis of 146 studies.

OBJECTIVES: Predictive models are increasingly used to support the clinical management of dengue, but their performance varies widely across settings....

Experts' Opinions on the Sustainable Use of Digital Health Tools for Effective Future Pandemic Preparedness and Response: Questionnaire Study.

BACKGROUND: The COVID-19 pandemic demonstrated the potential role of digital health tools in enhancing pandemic preparedness and response. These tools...

Predictive variables for early detection of sepsis in adults admitted to intensive care units: protocol for a systematic review.

INTRODUCTION: Sepsis is a life-threatening condition in intensive care units (ICUs), where any delay in diagnosis and treatment can lead to organ dysf...

Aligning neonatal sepsis triage diagnostics with WHO target product profiles in low- and middle-income countries.

Neonatal sepsis is a leading cause of infant morbidity and mortality in low- and middle-income countries (LMICs), yet despite this, progress in the de...