HIV/AIDS

Numerical approximation of fractional order HIV/AIDS model with treatment using Levenberg-Marquardt backpropagation approach.

HIV specifically targets the immune system's T cells, mainly the CD4+ T cells, leading to a chronic and severe illness characterized by a long incubation period. In this study, we propose a novel nonlinear fractional-order model for analyzing and controlling HIV proliferation dynamics. The model categorizes the HIV-infected population into four distinct compartments: susceptible individuals (S), a...

An interactive and explainable AI approach to improve human-machine teaming in cancer subtyping from digital cytopathology.

Algorithmic decision support is rapidly becoming a staple of personalized medicine, particularly for high-stakes recommendations such as cancer subtyping in which access to patient-specific information can drastically alter the course of treatment, and thus, patient outcome. To enhance the utility of decision support systems, it is vital to provide not just recommendations, but also contextual inf...

scMapNet: Marker-based cell type annotation of scRNA-seq data via vision transfer learning with tabular-to-image transformations.

INTRODUCTION: Identifying cell types is a key step in single-cell RNA sequencing data analysis that aids in understanding cellular heterogeneity and f...

Machine learning for food flavor prediction and regulation: models, data integration, and future perspectives.

BACKGROUND: Flavor is a central attribute of food quality, shaping consumer preferences and market performance. Traditional evaluation methods, such a...

Integrating network pharmacology and multidimensional bioinformatics: Mechanistic exploration of six food and medicine homology plants in coronary heart disease therapy.

Our study integrates network pharmacology with multiple bioinformatics approaches to systematically construct a framework for elucidating the therapeu...

Predicting neurobehavioral outcomes in people with HIV.

BACKGROUND: This study identified complex, multidimensional, longitudinal biopsychosocial (BPS) phenotypes (MLBPSPs) in people with HIV (PWH) and eval...

Comparative Evaluation of Radiomics and Deep Learning Models for Disease Detection in Chest Radiography.

The application of artificial intelligence (AI) in medical imaging has revolutionized diagnostic practices, enabling advanced analysis and interpretat...

MSA-LR: Enhancing multi-scale temporal dynamics in multivariate time series forecasting with low-rank self-attention.

Accurately forecasting multivariate time series requires effectively capturing intricate temporal dependencies across diverse scales. Existing deep le...

Empowering Patient Autonomy: The Role of Large Language Models (LLMs) in Scaffolding Informed Consent in Medical Practice.

The principle of (respect for) patient autonomy has traditionally emphasized independence in medical decision-making, reflecting a broader commitment ...

OCR: OmniNet-Fusion: A hybrid attention-based CNN-RNN model for multi-omics integration in precision cancer drug response prediction.

The growing complexity of cancer therapeutics challenges the use of state-of-the-art computational models for drug response prediction. Design and imp...

Utilizing a combined approach of machine learning and structure-based drug design principles to identify potential hits targeting SphK1.

Sphingosine kinase (SphK1) is acrucial enzyme that aids in the processing of sphingolipids by adding a phosphate group to sphingosine, converting it i...

Development and validation of the APEX-HBD SCORe: a multivariable prediction model for postoperative complications in patients undergoing shoulder arthroplasty.

BACKGROUND: The incidence of total shoulder arthroplasty (TSA) has risen significantly, driven by expanded indications. This study aims to derive and ...

Assessing Readability, Understandability, and Actionability of ACPA Educational Resources and Utility of LLMs to Improve Accessibility for Caregivers.

ObjectiveIt is important for parents and caregivers of children with cleft lip and/or palate to easily understand educational resources provided by th...

Comparative Designs Reveal Preferences for Human-Generated Rather Than AI-Generated art.

The evaluation of AI-generated art has seen increased interest after widespread access to AI-generated art (e.g., DALL-E or Stable Diffusion). While p...

Additive Manufacturing of Neuromorphic Systems.

Neuromorphic engineering aims to create brain-inspired computing systems based on synaptic electronic hardware and neural network software. It combine...

Machine Learning Algorithms Enhance the Accuracy of Radiographic Diagnosis of Dental Caries: A Comparative Study.

OBJECTIVES: This study evaluated the influence of cognitive aids, including machine learning (ML) algorithms and checklists, on the diagnostic accurac...

Predicting antiretroviral therapy adherence status of adult HIV-positive patients using machine-learning Northwest, Ethiopia, 2025.

BACKGROUND: Adherence with Anti-Retroviral Therapy (ART) reduces viral load, as well as HIV-related morbidity and mortality. Despite the expanded avai...

Identifying Health Care Services Offered in the HIV Care Continuum via a Machine Learning-Based Topic Modeling Approach: Exploratory Literature Review.

BACKGROUND: It remains unclear whether the existing health care services reflect the HIV care continuum, which underscores the need for integrated car...

AADNet: An End-to-End Deep Learning Model for Auditory Attention Decoding.

Auditory attention decoding (AAD) is the process of identifying the attended speech in a multi-talker environment using brain signals, typically recor...

Predicting SARS-CoV-2-specific CD4 and CD8 T-cell responses elicited by inactivated vaccines in healthy adults using machine learning models.

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highlights the importance of monitoring immune response...