Infectious Disease

Machine learning and the role of the vaginal and fecal microbiome in miscarriage: a matched case-control study.

Miscarriage occurs in approximately 15% of all pregnancies, and recent studies have suggested a potential role of the microbiome. A nested case-control study from the Swedish Maternal Microbiome cohort was conducted, including 34 participants who sent at least one vaginal or fecal microbiome sample and questionnaire data before miscarrying (n = 34), and matched controls (n = 105 for regression mod...

Visit-level prediction of missed HIV appointments using machine learning and transformer-based models in Uganda.

Artificial intelligence-based analysis of thrombotic and infectious risk factors in peripherally inserted central catheters (PICCs).

INTRODUCTION: Peripherally inserted central catheters (PICCs) are increasingly used in France for prolonged intravenous therapies such as chemotherapy...

A fuzzy time-series driven ensemble approach for accurate forecasting of higher education rankings.

The global education system comprises many technical and non-technical institutions. The selection of an institute plays a very important role in shap...

Precisely Identifying Growth Phases of Living Bacteria using Open-Set Deep Learning-Driven Single-Cell Raman Spectroscopy.

Owing to population cellular heterogeneity, it is still challenging to identify and determine the growth phases of spore-forming bacterial cells from ...

RaMoA: Raman Microspectroscopy and Deep Learning for the Classification of Antimicrobial Mechanism of Action.

We propose an innovative technology based on the combination of Raman microspectroscopy and deep learning to classify the Mechanism of Action (MoA) of...

Machine learning diagnostic framework for liver fibrosis in chronic hepatitis B based on routine laboratory tests.

Early detection of liver fibrosis in chronic hepatitis B (CHB) patients is crucial for improving their prognosis. This study aims to develop a machine...

Bayesian networks for predicting clinical outcomes in COVID-19 patients: A retrospective study in a resource-limited setting.

BACKGROUND: The COVID-19 pandemic has highlighted the critical need for robust, interpretable predictive models to guide clinical decision-making for ...

Genetic and clinical determinants of tacrolimus accumulation in early liver transplantation: evidence for a combined genotype-antibiotic effect.

BACKGROUND: Tacrolimus is a first-line immunosuppressant essential for preventing graft rejection after liver transplantation, but its narrow therapeu...

A comparative study of classical and neural network based optimal control in dengue transmission dynamics.

This study develops and analyses a mathematical model that represents dengue transmission between human and mosquito populations. The human population...

SEEK: A simple defense to model hijacking attack.

Model hijacking attacks represent an emerging training-time threat to natural language processing systems. They compromise the model's training proces...

Enhanced pneumonia prognosis via a hybrid deep learning ensemble: Dense Net, Efficient Net, and VGG16 integration.

Pneumonia, a prevalent and potentially life-threatening lung infection, requires rapid and precise diagnosis for effective treatment. Conventional cli...

FTIR spectroscopy of peripheral blood mononuclear cells and machine learning: Spectral biomarkers for bacteremia, focal bacterial, and viral infections.

The rapid and accurate differentiation of bacteremia, focal bacterial infections (FBI), and viral illnesses in febrile immunocompromised patients is a...

A Multidisciplinary Approach for Predicting the Microbiological Spoilage of Chicken Breast Fillets due to Cold-chain Disruption.

Cold-chain disruptions during storage and distribution of raw poultry can significantly reduce product shelf-life and safety. This study evaluated the...

Trends, Antimicrobial Resistance, and Source Attribution of Campylobacter jejuni and C. coli in Beijing: An 8-Year Molecular Surveillance Study.

OBJECTIVES: Beijing, a large urban center with complex food supply chains, faces increasing challenges from foodborne Campylobacter infections. Howeve...

Integrating explainable AI and One Health: a new frontier in combating infectious diseases.

Infectious diseases (IDs) remain a major threat to global health and societal stability. Because most emerging IDs in humans are zoonotic in origin an...

Non-polio enterovirus infection and electrophysiological changes in human iPSC-derived neural networks.

BACKGROUND: The non-polio enteroviruses (NPEV) enterovirus D68 (EV-D68) and enterovirus A71 (EV-A71) are highly prevalent and considered pathogens of ...

Quantification, radiomics and artificial intelligence in infection imaging: Current status and future directions in nuclear medicine.

Nuclear medicine infection imaging has traditionally relied on semantic visual interpretation supported by simple semi-quantitative indices. While eff...

Identifying Temporal Drivers for Microbial Community Assembly in Wastewater Treatment by Stochastic Physics-Informed Deep Learning Based on Limited-View and Sparsely Sampled Data.

Microbial community assembly (MCA) is the key to biological wastewater treatment by dynamically shaping the functional populations responsible for pol...

Rapid Proteome-Wide Discovery of Protein-Protein Interactions With ppIRIS.

Protein-protein interactions (PPIs) are central to cellular processes and host-pathogen dynamics across all domains of life, yet comprehensive interac...