Infectious Disease

Association between completing at least eight antenatal care contacts and maternal anaemia in Ghana: a cross-sectional study using causal machine learning.

BACKGROUND: Maternal anaemia remains a pressing global health challenge, with a notable burden in low- and middle-income countries. Existing studies in sub-Saharan Africa have largely relied on average associations, thereby concealing key variation among women and failing to account for heterogeneity. OBJECTIVE: To assess the association between completing at least eight antenatal care (ANC) conta...

A 19-layer convolutional neural network for accurate COVID-19 detection in chest X-ray images: comparative analysis with pretrained networks.

One of the most conspicuous developments in the unprecedented worldwide epidemic of COVID-19 is the pressing demand for reliable diagnostic tools. Utilizing artificial intelligence (AI) and image processing algorithms, this work proposes a novel 19-layer Convolutional Neural Network (CNN) for accurate COVID-19 detection from chest X-ray images. This CNN architecture supports structure with single/...

Predicting knowledge of cervical cancer screening among reproductive-age women in sub-saharan africa using machine learning algorithms.

Sub-Saharan Africa faces twice the incidence and up to fifteen times the fatality rate of cervical cancer compared to developed countries. Screening c...

Early antifungal resistance prediction based on MALDI-TOF mass spectrometry and machine learning.

Antimicrobial resistance (AMR) is a significant global health threat. Recent studies have shown that combining MALDI-TOF mass spectrometry with machin...

The prognostic value of the early neutrophil-to-lymphocyte ratio for 28-day mortality in sepsis patients: A machine learning-based investigation of the MIMIC database.

BACKGROUND: The neutrophil-to-lymphocyte ratio (NLR) has shown inconsistent prognostic value in individuals with sepsis. This study aimed to clarify i...

Threshold-dependent control of ARG removal in global wastewater treatment plants: Molecular mechanisms of low-abundance functional genes deciphered via metagenomics and explainable AI.

Wastewater treatment plants (WWTPs) serve as critical barriers against the dissemination of antibiotic resistance genes (ARGs) from urban water enviro...

Pattern dynamics and practical application of infectious disease reaction-diffusion systems based on higher-order networks and physics-informed neural networks.

Traditional epidemic models have limitations in capturing spatial heterogeneity, describing population-oriented migration, and integrating real data. ...

Identification of Pathological Secretions in Bronchoscopic Images Based on Edge Features and Multi-Scale Attention Mechanism.

The accumulation of pathological bronchial secretions compromises ventilation and oxygenation in critically ill patients and may lead to atelectasis o...

Data-Driven Prediction of Microbiological Quality in Oregano-Active Packaged Gilthead Sea Bream Fillets using Non-Invasive Spectroscopy and Machine Learning.

This study investigated the potential of FTIR spectroscopy and multispectral imaging (MSI) combined with machine learning to monitor microbiological q...

Characteristics of Plausible Source Cases Responsible for Recent Mycobacterium tuberculosis Transmission, United States, 2018-2022.

Tuberculosis (TB) outbreaks in the United States can cause substantial illness. Using surveillance and genotyping data, we applied a plausible source-...

Examining Selection Dynamics and Limitations in Multi-round Protein Selection of High Diversity Libraries.

Proteins and peptides underpin essential biological functions and technological applications, from targeting disease-relevant interactions to providin...

Attention-Guided Multi-View Contrastive Learning for Predicting Sparse Drug-Gene Associations.

Employing deep learning techniques for drug discovery and repurposing necessitates the acceleration of predictions regarding drug-gene interactions. H...

Human and Robot Assistance for Cognitive Load in Younger and Older Adults: Multimodal Within-Subject Experimental Study.

BACKGROUND: Maintaining cognitive efficiency and independence is a central goal of healthy aging. Socially assistive robots (SARs) are increasingly pr...

Population-Level Raman Biochemical Staging of Malaria in Human Red Blood Cells Using Interpretable Machine Learning.

Accurate malaria staging is vital for treatment decisions and monitoring of transmission. Because mature Plasmodium falciparum parasites sequester in ...

Machine learning-based prediction of antibiotic resistance gene distribution in agricultural soils under different climate change scenarios.

Antibiotic resistance genes (ARGs) in agricultural soils represent a major public health concern, as climate change is believed to augment their disse...

From Parasite to Pill: Harnessing Biology for Breakthroughs in Antimalarial Drug Discovery.

The global imperative for malaria eradication demands innovative strategies for antimalarial drug discovery, particularly in the face of growing drug ...

An artificial intelligence model for prediction of hepatocellular carcinoma risk in patients with chronic hepatitis C.

Hepatocellular carcinoma (HCC) still occurs in patients with hepatitis C who achieved sustained virologic response (SVR) after direct-acting antiviral...

Overcoming resolution constraints in automated colony counting via a high-performance deep learning framework using SAHI.

Lightweight models perform poorly in bacterial colony counting when high-resolution Petri dish images are downscaled to 640 × 640 pixels. This study a...

AI for predicting exacerbations in KIDs with asthma (AIRE-KIDS).

Recurrent acute care visits are a common yet preventable outcome for many children with asthma. Machine learning (ML) applied to electronic medical re...

Automating infection indicator extraction in home healthcare through instruction-tuned large language models.

OBJECTIVE: Home healthcare (HHC) clinical notes contain critical infection indicators that clinicians need in structured "indicator + context" pairs. ...