COVID-19

The role of biopsychosocial factors in classifying pain intensity across various chronic pain conditions.

Chronic pain is a multifaceted condition shaped by biological, psychological, and social factors, which challenges its diagnosis and treatment. While prior research largely focused on sensory profiles to distinguish pain mechanisms, this study adopted a biopsychosocial perspective with the key addition of experimental pain paradigms to identify factors explaining variance in chronic pain severity ...

YOLOv10-based multi-scale variant object detection for multi-category PPE non-compliance monitoring on construction sites.

Multi-category Personal Protective Equipment (PPE) non-compliance monitoring on construction sites remains challenging because visual cues for missing PPE often appear at multiple scales, particularly as small objects. To address these challenges, an enhanced YOLOv10-based detector is developed that incorporates Omni-Dimensional Dynamic Convolution (ODConv) to strengthen fine-grained feature repre...

Development and validation of a noninvasive machine learning model using urinary extracellular vesicle physical parameters for prostate cancer diagnosis.

Urinary extracellular vesicles (uEVs) are promising biomarkers for prostate cancer (PCa). Although novel uEV-based biomarkers have advanced early diag...

EEG biomarkers can predict early-stage Alzheimer's disease and correlate with intracerebral pathology: a multimodal machine learning study.

BACKGROUND: Early recognition of Alzheimer's disease (AD) is crucial for timely intervention and delaying disease progression. Electroencephalogram (E...

Machine learning models based on magnetic resonance imaging for predicting Lymphovascular Invasion in Invasive Breast Cancer.

OBJECTIVES: Treatment strategies for invasive breast cancer require accurate lymphovascular invasion (LVI) predictions. This study aimed to investigat...

Translating transcriptomics analysis into diagnostic workflows: clinical variant identification and interpretation in hypothesis-driven and hypothesis-free approaches.

BACKGROUND: Despite significant advancements in genetic diagnosis, there are still bottlenecks in DNA-level testing. Challenges to diagnosis include t...

Lactylation-related prognostic signature characterized in pancreatic ductal adenocarcinoma through public scRNA-seq dataset and machine learning algorithms: the TOP2A-H3K18la-NQO1 axis orchestrates malignant progression.

BACKGROUND: Lactate promotes histone lactylation, which affects protein transcription and translation, thereby influencing tumour cell progression. Ho...

Demographic prompt cues shift clinical recommendations in multimodal large language models: a multi-model audit of 25,380 dental radiograph assessments.

BACKGROUND: Multimodal large language models (LLMs) are increasingly being evaluated for clinical image interpretation, but whether patient demographi...

Precision Management of Autoimmune Ocular Complications: Th17 Mechanisms and Therapeutic Innovations.

Precision management of ocular complications in systemic autoimmune diseases, such as Sjögren's syndrome (SS), systemic lupus erythematosus (SLE), Beh...

Application of surface-enhanced Raman spectroscopy in the diagnosis of infectious diseases.

Surface-enhanced Raman spectroscopy (SERS) is increasingly emerging as a pivotal analytical technique in the field of clinical diagnostics. The diagno...

Post-quantum cognitive zero trust architecture for healthcare IoT devices.

Healthcare IoT systems increasingly rely on interconnected, resource-constrained devices that are vulnerable to both classical and emerging quantum-en...

Prediction of antibody non-specificity using protein language models and biophysical parameters.

The development of therapeutic antibodies requires optimizing target binding affinity and pharmacodynamics, while ensuring high developability potenti...

The utility of artificial intelligence for DNA variant curation in the Mendelian genetic disorder familial hypercholesterolaemia.

The assessment of DNA sequence variants for biological function and their classification into risk categories is time-consuming. This has widened the ...

A machine learning-based interpretable model for predicting pancreatic cancer in chronic pancreatitis patients with focal pancreatic lesions.

BACKGROUND: Pancreatic cancer (PC) is deadly and distinguishing it from inflammatory conditions in chronic pancreatitis (CP) patients is challenging. ...

Multimodal Genotype-Phenotype Analysis in SMARCB1-Associated Developmental Disorders.

PURPOSE: Variants in SMARCB1, encoding a core subunit of the BAF chromatin remodeling complex, are associated with intellectual developmental disorder...

Elucidating CO2 dynamics in high-entropy MOF-74 via machine learning interatomic potentials.

High entropy variants of MOF-74 have demonstrated enhanced CO2 adsorption performance, yet it remains unclear whether homogenous metal mixing alone pr...

Comparative machine learning for accurate EEG-based epileptic seizure state classification using sub-band analysis.

Timely identification of seizure-related EEG states can support clinical assessment and motivate future monitoring tools. This study investigates a co...

Beyond Time Saved: Implementation, Equity, and the Utility Threshold for Nursing AI Scribes.

Schwabe et al's pre-post time-motion study of a domain-specific artificial intelligence (AI) speech assistant used by nurses in German long-term care ...

Delta feature and random forest-enhanced LSTM-attention forecasts with probabilistic postprocessing for rainfall forecasting.

Reliable rainfall forecasts are crucial for real-time flood control and managing water resources. Advances in deep learning, high-performance computin...

Predicting sleep state from continuous positive airway pressure flow in patients with obstructive sleep apnea.

INTRODUCTION: The first line treatment for obstructive sleep apnea (OSA) is continuous positive airway pressure (CPAP). CPAP adherence is assessed by ...