Infectious Disease

Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning.

While the useful armory of antibiotic drugs is continually depleted due to the emergence of drug-resistant pathogens, the development of novel therapeutics has also slowed down. In the era of advanced computational methods, approaches like machine learning (ML) could be one potential solution to help reduce the high costs and complexity of antibiotic drug discovery and attract collaboration across...

AI-MET: A deep learning-based clinical decision support system for distinguishing multisystem inflammatory syndrome in children from endemic typhus.

The COVID-19 pandemic brought several diagnostic challenges, including the post-infectious sequelae multisystem inflammatory syndrome in children (MIS-C). Some of the clinical features of this syndrome can be found in other pathologies such as Kawasaki disease, toxic shock syndrome, and endemic typhus. Endemic typhus, or murine typhus, is an acute infection treated much differently than MIS-C, so ...

Peptide classification landscape: An in-depth systematic literature review on peptide types, databases, datasets, predictors architectures and performance.

Peptides are gaining significant attention in diverse fields such as the pharmaceutical market has seen a steady rise in peptide-based therapeutics ov...

A hybrid inception-dilated-ResNet architecture for deep learning-based prediction of COVID-19 severity.

Chest computed tomography (CT) scans are essential for accurately assessing the severity of the novel Coronavirus (COVID-19), facilitating appropriate...

Improving Malaria diagnosis through interpretable customized CNNs architectures.

Malaria, which is spread via female Anopheles mosquitoes and is brought on by the Plasmodium parasite, persists as a serious illness, especially in ar...

AI-augmented Biophysical modeling in thermoplasmonics for real-time monitoring and diagnosis of human tissue infections.

Identifying tissue infections from the body still poses an unprecedented challenge in society. Conventional diagnostic procedures are time-consuming a...

A predictive study on HCV using automated machine learning models.

Hepatitis C virus (HCV) infection represents a significant contributor to chronic liver disease on a global scale. The prompt identification and manag...

Machine learning detection of heteroresistance in Escherichia coli.

BACKGROUND: Heteroresistance (HR) is a significant type of antibiotic resistance observed for several bacterial species and antibiotic classes where a...

Disease diagnostics using machine learning of B cell and T cell receptor sequences.

Clinical diagnosis typically incorporates physical examination, patient history, various laboratory tests, and imaging studies but makes limited use o...

Prioritizing Trust in Podiatrists' Preference for AI in Supportive Roles Over Diagnostic Roles in Health Care: Qualitative Interview and Focus Group Study.

BACKGROUND: As artificial intelligence (AI) evolves, its roles have expanded from helping out with routine tasks to making complex decisions, once the...

Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model.

BACKGROUND: In March 2022, a new outbreak of COVID-19 emerged in Quanzhou, leading to the implementation of strict lockdown management measures in col...

Predicting the Risk of HIV Infection and Sexually Transmitted Diseases Among Men Who Have Sex With Men: Cross-Sectional Study Using Multiple Machine Learning Approaches.

BACKGROUND: Men who have sex with men (MSM) are at high risk for HIV infection and sexually transmitted diseases (STDs). However, there is a lack of a...

IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition.

Deaf and hard-of-hearing people utilize sign language recognition (SLR) to interconnect. Sign language (SL) is vital for hard-of-hearing and deaf indi...

ML-AMPs designed through machine learning show antifungal activity against C. albicans and therapeutic potential on mice model with candidiasis.

AIMS: C. albicans resistant strains have led to increasingly severe treatment challenges. Antimicrobial peptides with low resistance-inducing propensi...

RAG_MCNNIL6: A Retrieval-Augmented Multi-Window Convolutional Network for Accurate Prediction of IL-6 Inducing Epitopes.

Interleukin-6 (IL-6) is a critical cytokine involved in immune regulation, inflammation, and the pathogenesis of various diseases, including autoimmun...

Freeze-Thaw Imaging for Microorganism Classification Assisted with Artificial Intelligence.

Fast and cost-effective microbial classification is crucial for clinical diagnosis, environmental monitoring, and food safety. However, traditional me...

Artificial intelligence for modelling infectious disease epidemics.

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related te...

Impact of Sepsis Onset Timing on All-Cause Mortality in Acute Pancreatitis: A Multicenter Retrospective Cohort Study.

BackgroundSepsis complicates acute pancreatitis (AP), increasing mortality risk. Few studies have examined how sepsis and its onset timing affect mort...

T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein-Ligand Binding Affinity Prediction with Uncertainty-Aware Self-Learning for Protein-Specific Alignment.

There is significant interest in targeting disease-causing proteins with small molecule inhibitors to restore healthy cellular states. The ability to ...

A web-based artificial intelligence system for label-free virus classification and detection of cytopathic effects.

Identifying viral replication within cells demands labor-intensive isolation methods, requiring specialized personnel and additional confirmatory test...