COVID-19

Graph Convolutional Neural Network based Depression Detection using Brain Functional Connectivity Measures.

The structural and functional connectivity of the brain network is a combination of complex connections and interconnections among neurons of different brain regions. Analysis of these connectivity patterns provides a representation of the mental health of an individual, including major depressive disorder (MDD). MDD analysis with Electroencephalogram (EEG) has increasingly focused on characterizi...

Operationalizing Digital Health Equity in Artificial Intelligence-Enabled Patient Decision Aids for Older Adults: Mixed Methods Study.

BACKGROUND: Artificial intelligence-enabled patient decision aids (AI-PDAs) hold promise for supporting older adults with chronic diseases in accessing personalized health information, clarifying preferences, and engaging in shared decision-making. Achieving equity in their design requires attention to the complex health care and digital contexts in which these tools are used. While the Digital He...

Somatic variant-calling beyond cancer: Repurposing algorithms to map low‑allele‑fraction variants across genomics.

BACKGROUND: Somatic variant callers were originally developed to identify tumour-specific mutations in mixed tumour-normal samples. Increasingly, disc...

Constructing regulatory networks of Rubisco post-translational modifications: a novel avenue for engineering environment adaptive plants.

Chloroplastic proteins play pivotal roles in optimizing photosynthesis, particularly under fluctuating environmental conditions. Ribulose-1,5-bisphosp...

Bacterial keratitis: a global review of current practices, challenges and innovations.

Bacterial keratitis is a major cause of corneal blindness worldwide, with marked differences in clinical presentation and risk factors across regions....

Explainable artificial intelligence reveals divergent learning in pharmacophore-based hierarchical pooling graph neural networks.

Hierarchical pooling is a promising mechanism to enhance graph neural networks (GNNs) by enabling multi-scale representation learning. Rationalization...

Identification and validation of biomarkers associated with mitochondria and glycometabolism in gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) can elevate the likelihood of developing high blood pressure during pregnancy. It is one of the most common compli...

An interpretable machine learning model integrating peripheral blood lncRNAs and clinical variables for phase classification in chronic myeloid leukemia.

BACKGROUND: Accurate disease phase assessment remains clinically important in chronic myeloid leukemia (CML), as progression to accelerated or blast p...

Growth factor thermostability dataset derived from experimental and computational approaches to accelerate cultured meat development.

This project compiled experimentally measured and computationally predicted thermostability data for growth factors (GFs) commonly used in cultured me...

Machine learning approaches to identify genetic markers for goat climatic adaptation.

UNLABELLED: Whole-genome SNP data from 109 goats, including 55 indigenous Indian goats and 54 exotic goats, were analyzed to identify ancestry informa...

Equity-by-design for socially assistive robots as digital health tools.

OBJECTIVES: To propose an equity-by-design agenda for socially assistive robots (SARs) as embodied digital health informatics interventions. MATERIALS...

Artificial intelligence-enhanced nurse navigation for monitoring and care of long COVID.

INTRODUCTION: Long COVID is a multisystem condition with challenging diagnosis. Nurse-navigation, a patient-centered intervention, can enhance educati...

Pan-cancer analysis identifies immunoproteasome as the predominant survival-associated component of antigen processing machinery.

Neoantigens are critical targets for cancer immunotherapy, yet the relationship between experimentally validated neoantigen burden and antigen process...

Tephritid26: A standardized, multi-angle image dataset of quarantine-significant true fruit flies for deep learning-based identification.

Accurate and rapid identification of quarantine-significant tephritids is critical to global agricultural biosecurity, but the application of deep lea...

A Robust Voice-Based Parkinson's Disease Diagnosis Model via Semantic RGB Feature Transformation and Hybrid Deep Learning.

Reliable diagnosis of Parkinson's disease (PD) in its early stages is of vital importance for supporting timely clinical decision-making and improving...

AI-assisted digital breast tomosynthesis as a decision-support tool for post-neoadjuvant surgical planning in breast cancer.

PURPOSE: Accurate assessment of residual disease after neoadjuvant chemotherapy (NAC) is essential for surgical planning and prevention of incomplete ...

Enhancing the severity classification of tomato plant epidemic pathogens using adaptive segmentation of mask RCNN and multiscale recurrent MobileNet.

Tomatoes are the most significant and widely consumed crops globally. Leaf diseases cause an important threat to crop production and quality. Further,...

Novel Alzheimer's disease-associated variants and genetic interactions identified from UK biobank whole-exome sequencing data using IBI-DT.

Alzheimer's disease (AD) is a highly heritable neurodegenerative disorder whose genetic architecture remains incompletely understood, particularly wit...

Near-perfect genome sequencing in medical genetics.

Medical genetics currently operates through a fragmented diagnostic cascade built around short-read sequencing technologies that carry well-documented...

Decoding splicing variants in high-throughput sequencing: a functional validation approach integrating deep learning tools.

High-throughput genome and exome sequencing have uncovered numerous intronic variants in disease genes, yet predicting their impact on pre-mRNA splici...