Infectious Disease

Enhancing parasitic organism detection in microscopy images through deep learning and fine-tuned optimizer.

Parasitic organisms pose a major global health threat, mainly in regions that lack advanced medical facilities. Early and accurate detection of parasitic organisms is vital to saving lives. Deep learning models have uplifted the medical sector by providing promising results in diagnosing, detecting, and classifying diseases. This paper explores the role of deep learning techniques in detecting and...

Deep-learning assisted zwitterionic magnetic immunochromatographic assays for multiplex diagnosis of biomarkers.

Magnetic nanoparticle (MNP)-based immunochromatographic tests (ICTs) display long-term stability and an enhanced capability for multiplex biomarker detection, surpassing conventional gold nanoparticles (AuNPs) and fluorescence-based ICTs. In this study, we innovatively developed zwitterionic silica-coated MNPs (MNP@Si-Zwit/COOH) with outstanding antifouling capabilities and effectively utilised th...

Machine learning models for the early prediction of ventilator-associated pneumonia: Author's reply.

Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation.

Impedance flow cytometry (IFC) has been demonstrated to be an efficient tool for label-free bacterial investigation to obtain the electrical propertie...

Deep learning model for personalized prediction of positive MRSA culture using time-series electronic health records.

Methicillin-resistant Staphylococcus aureus (MRSA) poses significant morbidity and mortality in hospitals. Rapid, accurate risk stratification of MRSA...

Long-term reduced functional capacity and quality of life in hospitalized COVID-19 patients.

BACKGROUND: Persistent symptoms and exercise intolerance have been reported after COVID-19, even months after the acute disease. Although, the long-te...

Riboformer: a deep learning framework for predicting context-dependent translation dynamics.

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range ...

From CNN to Transformer: A Review of Medical Image Segmentation Models.

Medical image segmentation is an important step in medical image analysis, especially as a crucial prerequisite for efficient disease diagnosis and tr...

Advanced hybrid attention-based deep learning network with heuristic algorithm for adaptive CT and PET image fusion in lung cancer detection.

Lung cancer is one of the most deadly diseases in the world. Lung cancer detection can save the patient's life. Despite being the best imaging tool in...

Chemical multiscale robotics for bacterial biofilm treatment.

A biofilm constitutes a bacterial community encased in a sticky matrix of extracellular polymeric substances. These intricate microbial communities ad...

Applying explainable artificial intelligence methods to models for diagnosing personal traits and cognitive abilities by social network data.

This study utilizes advanced artificial intelligence techniques to analyze the social media behavior of 1358 users on VK, the largest Russian online s...

Machine learning and genetic algorithm-guided directed evolution for the development of antimicrobial peptides.

INTRODUCTION: Antimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics, possess a variety of potent biological activities an...

Construction of an aerolysin-based multi-epitope vaccine against an machine learning and artificial intelligence-supported approach.

, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroe...

Deep Learning Radiomics Analysis of CT Imaging for Differentiating Between Crohn's Disease and Intestinal Tuberculosis.

This study aimed to develop and evaluate a CT-based deep learning radiomics model for differentiating between Crohn's disease (CD) and intestinal tube...

Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation.

BACKGROUND: With increasing antibiotic resistance and regulation, the issue of antibiotic combination has been emphasised. However, antibiotic combina...

CODENET: A deep learning model for COVID-19 detection.

Conventional COVID-19 testing methods have some flaws: they are expensive and time-consuming. Chest X-ray (CXR) diagnostic approaches can alleviate th...

Machine Learning Accelerates De Novo Design of Antimicrobial Peptides.

Efficient and precise design of antimicrobial peptides (AMPs) is of great importance in the field of AMP development. Computing provides opportunities...

PulmoNet: a novel deep learning based pulmonary diseases detection model.

Pulmonary diseases are various pathological conditions that affect respiratory tissues and organs, making the exchange of gas challenging for animals ...

Siamese Networks for Clinically Relevant Bacteria Classification Based on Raman Spectroscopy.

Identifying bacterial strains is essential in microbiology for various practical applications, such as disease diagnosis and quality monitoring of foo...

Transformative Deep Neural Network Approaches in Kidney Ultrasound Segmentation: Empirical Validation with an Annotated Dataset.

Kidney ultrasound (US) images are primarily employed for diagnosing different renal diseases. Among them, one is renal localization and detection, whi...