HIV/AIDS

Urine kidney injury molecule-1 predicts subclinical kidney disease among persons living with HIV initiating tenofovir disoproxil fumarate-based ART in Zambia.

INTRODUCTION: Antiretroviral therapy (ART) increases the life expectancy of persons living with HIV (PLWH), but not without potentially serious adverse effects. Tenofovir disoproxil fumarate (TDF) can cause nephrotoxicity, manifesting as acute kidney injury (AKI) that may persist after treatment discontinuation. Kidney injury biomarkers such as kidney injury molecule-1 (KIM-1), retinol-binding pro...

Cognitive load detection through EEG lead wise feature optimization and ensemble classification.

Cognitive load stimulates neural activity, essential for understanding the brain's response to stress-inducing stimuli or mental strain. This study examines the feasibility of evaluating cognitive load by extracting, selection, and classifying features from electroencephalogram (EEG) signals. We employed robust local mean decomposition (R-LMD) to decompose EEG data from each channel, recorded over...

Ethical engagement with artificial intelligence in medical education.

The integration of large language models (LLMs) in medical education offers both opportunities and challenges. While these artificial intelligence (AI...

STI/HIV risk prediction model development-A novel use of public data to forecast STIs/HIV risk for men who have sex with men.

A novel automatic framework is proposed for global sexually transmissible infections (STIs) and HIV risk prediction. Four machine learning methods, na...

Deaf futurity: designing and innovating hearing aids.

One of the tenets of a posthuman vision is the eradication of disability through technology. Within this site of 'no future', as Alison Kafer describe...

Deciphering the cellular and molecular landscape of pulmonary fibrosis through single-cell sequencing and machine learning.

Pulmonary fibrosis is characterized by progressive lung scarring, leading to a decline in lung function and an increase in morbidity and mortality. Th...

Assessing the environmental determinants of micropollutant contamination in streams using explainable machine learning and network analysis.

Even at trace concentrations, micropollutants, including pesticides and pharmaceuticals, pose considerable ecological risks, and the increasing presen...

In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes.

Diabetes represents a significant global health challenge associated with substantial healthcare costs and therapeutic complexities. Current diabetes ...

AI-Driven insights in pancreatic cancer imaging: from pre-diagnostic detection to prognostication.

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in the United States, largely due to its poor five-year su...

Developing a fully applicable machine learning (ML) based sex classification model using linear cranial dimensions.

Recent advances in artificial intelligence (AI) and machine learning (ML) applications have elevated accomplishments in various scientific fields, pri...

Leveraging fuzzy embedded wavelet neural network with multi-criteria decision-making approach for coronary artery disease prediction using biomedical data.

Coronary artery disease (CAD) is the main cause of death. It is a complex heart disease that is linked with many risk factors and a variety of symptom...

Application of deep learning models on single-cell RNA sequencing analysis uncovers novel markers of double negative T cells.

Double negative T (DNT) cells are a unique subset of CD3 + TCRαβ + T lymphocytes that lack CD4, CD8, or NK1.1 expression and constitute 3-5% of the to...

Emotion recognition using multi-scale EEG features through graph convolutional attention network.

Emotion recognition via electroencephalogram (EEG) signals holds significant promise across various domains, including the detection of emotions in pa...

Methodology for Safe and Secure AI in Diabetes Management.

The use of artificial intelligence (AI) in diabetes management is emerging as a promising solution to improve the monitoring and personalization of th...

AI-Enhanced Healthcare: Integrating ChatGPT-4 in ePROs for Improved Oncology Care and Decision-Making: A Pilot Evaluation.

BACKGROUND: Since 2023, ChatGPT-4 has been impactful across several sectors including healthcare, where it aids in medical information analysis and ed...

CircWaveDL: Modeling of optical coherence tomography images based on a new supervised tensor-based dictionary learning for classification of macular abnormalities.

Modeling Optical Coherence Tomography (OCT) images is crucial for numerous image processing applications and aids ophthalmologists in the early detect...

Machine learning approach and geospatial analysis to determine HIV infection, awareness status, and transmission knowledge among adults in Sub-Saharan Africa.

BACKGROUND: HIV/AIDS remains a major public health challenge, in Sub-Saharan Africa (SSA). In 2020, 16% of people living with HIV did not know their H...

Machine learning analysis of CD4+ T cell gene expression in diverse diseases: insights from cancer, metabolic, respiratory, and digestive disorders.

CD4 T cells play a pivotal role in the immune system, particularly in adaptive immunity, by orchestrating and enhancing immune responses. CD4 T cell-r...

Evaluation of hypoxia-inducible factor-1α and urine non-transferrin-bound iron concentrations in cats with chronic kidney disease.

INTRODUCTION: Hypoxia-inducible factors (HIF) regulate gene transcription, which aids hypoxia adaptation while promoting renal fibrosis. Non-transferr...

Determining structures of RNA conformers using AFM and deep neural networks.

Much of the human genome is transcribed into RNAs, many of which contain structural elements that are important for their function. Such RNA molecules...