Infectious Disease

Liver cancer risk stratification using deep learning on nationwide longitudinal health screening data: a retrospective cohort study.

BACKGROUND: Current liver cancer screening in Korea focuses on viral hepatitis or cirrhosis, despite rising risks from metabolic and alcohol-related liver disease. We aimed to develop a deep learning model that leverages routinely collected national screening and claims data to predict liver cancer risk without requiring additional diagnostic tests. METHODS: We conducted a retrospective cohort stu...

Innovative application of a traffic-prediction spatio-temporal graph convolutional network for dengue disease forecasting.

A novel hypothetical protein (SAUSA300_1684) confers excellent protection against multi-drug-resistant Staphylococcus aureus infection in the murine model.

Staphylococcus aureus is a leading cause of nosocomial infections, including sepsis, bacteraemia, pneumonia, and endocarditis, and continues to pose a...

Construction of a diagnostic model for tuberculosis based on long non-coding RNA.

BACKGROUND: The World Health Organization encourages the development of novel diagnostic tools based on 'non-sputum' samples to meet global goals for ...

Substrate-mediated trade-offs between pollutant removal efficiency and ecological risks in constructed wetlands treating multi-antibiotic wastewater.

The environmental dissemination of antibiotic resistance genes (ARGs) is a cornerstone of the One Health crisis, linking human, animal, and environmen...

Deconstruction by C. thermocellum-from microbe mediated to dynamic redistribution of cellulosomes.

Clostridium thermocellum is one of the most efficient microorganisms for the deconstruction of cellulosic biomass. To achieve this high level of cellu...

Predicting epistasis across proteins by structural logic.

Accurately predicting the phenotypic consequences of genetic variation is a major challenge for precision medicine. The problem is exacerbated by epis...

Multisequence MRI Enables High-Fidelity FDG-PET Synthesis for Epilepsy Using GANs.

BACKGROUND: FDG-PET aids presurgical epilepsy evaluation but is limited by access and radiation exposure. PURPOSE: To evaluate synthetic FDG-PET gener...

Stratification of viral shedding patterns in saliva of COVID-19 patients.

Living with COVID-19 requires continued vigilance against the spread and emergence of variants of concern (VOCs). Rapid and accurate saliva diagnostic...

AI-Assisted Multiplex SYBR Green I-Based qPCR for the Identification and Quantitative Analysis of Oral Microbiota.

Conventional multiplex qPCR faces challenges in quantitative multipathogen detection due to limited fluorescent channels, primer interference, and the...

Grape expectations: disentangling environmental drivers of microbiome establishment in winegrowing ecosystems.

Microbial communities play a central role in viticulture, influencing wine characteristics (a concept termed microbial terroir). Yet, the individual f...

Plasma glutamic acid predicts myelosuppression and mortality in septic patients using machine learning.

Myelosuppression is a common secondary manifestation of sepsis and is associated with increased morbidity and mortality. Recent evidence suggests that...

Foundation models enable wearable signal screening for cardiovascular disease among people living with HIV.

BACKGROUND: Cardiovascular disease screening faces significant challenges in resource-limited settings, where infrastructure and computational constra...

An interpretable machine learning model for prediction of significant liver fibrosis in comorbid chronic hepatitis B and nonalcoholic fatty liver disease: a retrospective development and validation study.

Ai derivation and exploration of antibiotic class spaces.

PURPOSE: The rapid evolution of antibiotic-resistant bacteria poses an urgent global health crisis. A key gap in current antibiotic discovery approach...

Predictive modeling and spatiotemporal analysis of TB in Argentina: Advancing control efforts through machine learning.

OBJECTIVES: To improve prediction and understanding of TB dynamics in Argentina, identifying key risk factors and high-incidence areas to inform surve...

Diagnostic Accuracy of the National Library of Medicine (NLM) Screener Application in Screening for Malaria Parasites Among Blood Donors at the Korle-Bu Blood Bank, Ghana: A Cross-Sectional Study.

BACKGROUND AND AIMS: Malaria is a deadly disease spread through the bite of an infected female Anopheles mosquito and remains the leading cause of mor...

A Machine Learning-Based Dynamic SST Index for Long-Lead Malaria Prediction in the Peruvian Amazon.

Malaria imposes a major health burden in the Peruvian Amazon, and its early warning is essential for effective disease prevention. The tropical sea su...

Prognostic Significance of Computed Tomography Severity Score for Machine Learning Prediction of Intensive Care Unit Admission in COVID-19 Patients.

OBJECTIVE: The computed tomography-severity score (CT-SS) quantifies the severity of pulmonary involvement and is significantly associated with diseas...

Artificial Intelligence in Pleural Diseases: Current Applications and Next Steps.

Pleural diseases pose a significant burden on healthcare systems due to diagnostic challenges and high costs. Artificial intelligence (AI) has the pot...