HIV/AIDS

Screening for Potential Antiviral Compounds from Cyanobacterial Secondary Metabolites Using Machine Learning.

The secondary metabolites of seawater and freshwater blue-green algae are a rich natural product pool containing diverse compounds with various functions, including antiviral compounds; however, high-efficiency methods to screen such compounds are lacking. Advanced virtual screening techniques can significantly reduce the time and cost of novel antiviral drug identification. In this study, we used...

Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning.

This study explored the pathogenesis of human immunodeficiency virus (HIV) and monkeypox co-infection, identifying candidate hub genes and potential drugs using bioinformatics and machine learning. Datasets for HIV (GSE 37250) and monkeypox (GSE 24125) were obtained from the GEO database. Common differentially expressed genes (DEGs) in co-infection were identified by intersecting DEGs from monkeyp...

A deep learning algorithm that aids visualization of femoral neck fractures and improves physician training.

PURPOSE: Missed fractures are the most common radiologic error in clinical practice, and erroneous classification could lead to inappropriate treatmen...

A Collaborative Multimodal Learning-Based Framework for COVID-19 Diagnosis.

The pandemic of coronavirus disease 2019 (COVID-19) has led to a global public health crisis, which caused millions of deaths and billions of infectio...

Antiviral Peptide-Generative Pre-Trained Transformer (AVP-GPT): A Deep Learning-Powered Model for Antiviral Peptide Design with High-Throughput Discovery and Exceptional Potency.

Traditional antiviral peptide (AVP) discovery is a time-consuming and expensive process. This study introduces AVP-GPT, a novel deep learning method u...

Enhancing Situational Awareness with VAS-Compass Net for the Recognition of Directional Vehicle Alert Sounds.

People with hearing impairments often face increased risks related to traffic accidents due to their reduced ability to perceive surrounding sounds. G...

Predicting Treatment Outcomes in Patients with Drug-Resistant Tuberculosis and Human Immunodeficiency Virus Coinfection, Using Supervised Machine Learning Algorithm.

Drug-resistant tuberculosis (DR-TB) and HIV coinfection present a conundrum to public health globally and the achievement of the global END TB strateg...

Machine Learning-Driven Data Valuation for Optimizing High-Throughput Screening Pipelines.

In the rapidly evolving field of drug discovery, high-throughput screening (HTS) is essential for identifying bioactive compounds. This study introduc...

The emerging role of artificial intelligence in neuropathology: Where are we and where do we want to go?

The field of neuropathology, a subspecialty of pathology which studies the diseases affecting the nervous system, is experiencing significant changes ...

Pre-training strategy for antiviral drug screening with low-data graph neural network: A case study in HIV-1 K103N reverse transcriptase.

Graph neural networks (GNN) offer an alternative approach to boost the screening effectiveness in drug discovery. However, their efficacy is often hin...

BioTRY: A Comprehensive Knowledge Base for Titer, Rate, and Yield of Biosynthesis.

Synthetic biology is rapidly evolving into a data-intensive science that increasingly relies on massive data sets; one of its applications is the eval...

Explainable artificial intelligence and domain adaptation for predicting HIV infection with graph neural networks.

OBJECTIVE: Investigation of explainable deep learning methods for graph neural networks to predict HIV infections with social network information and ...

Machine learning-derived peripheral blood transcriptomic biomarkers for early lung cancer diagnosis: Unveiling tumor-immune interaction mechanisms.

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection and a comprehensive understanding of tumor-immune...

Identification of novel biomarkers for atherosclerosis using single-cell RNA sequencing and machine learning.

Atherosclerosis (AS) is a predominant etiological factor in numerous cardiovascular diseases, with its associated complications such as myocardial inf...

The first AI-based Chatbot to promote HIV self-management: A mixed methods usability study.

BACKGROUND: We developed MARVIN, an artificial intelligence (AI)-based chatbot that provides 24/7 expert-validated information on self-management-rela...

A deep drug prediction framework for viral infectious diseases using an optimizer-based ensemble of convolutional neural network: COVID-19 as a case study.

The SARS-CoV-2 outbreak highlights the persistent vulnerability of humanity to epidemics and emerging microbial threats, emphasizing the lack of time ...

HIV-1 M group subtype classification using deep learning approach.

Traditionally, the classification of HIV-1 M group subtypes has depended on statistical methods constrained by sample sizes. Here HIV-1-M-SPBEnv was p...

A radiographic artificial intelligence tool to identify candidates suitable for partial knee arthroplasty.

INTRODUCTION: Knee osteoarthritis is a prevalent condition frequently necessitating knee replacement surgery, with demand projected to rise substantia...

An empirical study for mitigating sustainable cloud computing challenges using ISM-ANN.

The significance of cloud computing methods in everyday life is growing as a result of the exponential advancement and refinement of artificial techno...

Analog Spiking U-Net integrating CBAM&ViT for medical image segmentation.

SNNs are gaining popularity in AI research as a low-power alternative in deep learning due to their sparse properties and biological interpretability....