Anemia

Artificial Intelligence in Hemodialysis: Current Clinical Applications and Future Perspectives.

INTRODUCTION: Timely adjustment of intervention strategies based on multidimensional hemodialysis data is essential for improving patients' quality of life, enhancing clinical outcomes, and reducing complications. However, conventional management (relying heavily on clinician experience and intermittent monitoring) often fails to provide personalized, real-time, and proactive care. Efficient, data...

Dual-stream learning with inverted transformer and BiGRU for rolling bearing remaining useful life prediction.

Predicting the remaining useful life (RUL) of rolling bearings is essential for ensuring the reliability and safety of rotating machinery. However, accurate RUL prediction remains challenging due to the non-stationary degradation behavior of bearings operating under complex and time-varying conditions. Existing deep learning approaches often suffer from two key limitations: conventional Transforme...

Machine learning-based risk assessment of neonatal perinatal adverse outcomes of anemia during pregnancy: a modeling study.

BACKGROUND: Gestational anemia significantly elevates the risk of adverse maternal and neonatal outcomes, necessitating early predictive tools for tar...

From muscles to motion: the role of sensor layout and physiological factors in hand motion decoding.

Despite substantial progress in decoding biosignals for human motion prediction, the influence of participant- and experiment-related factors on the d...

Post-stroke rehabilitation in inflammatory rheumatic diseases: outcome measures, digital tools, and patient education perspectives.

Inflammatory rheumatic diseases (IRDs) represent a significant risk factor for cerebrovascular events, independent of traditional cardiovascular risk ...

Predictive analytics and risk stratification models in internal medicine: from risk scores to real-time machine learning.

Internal medicine involves high-stakes, time-sensitive decisions (such as triaging acute illnesses, escalating care, providing thromboprophylaxis, pla...

Machine Learning-Based Prediction of Track Sprint Cycling Performance in Elite-Level Male Cyclists: A Multinational Cross-Sectional Analysis.

BACKGROUND: Traditional linear approaches may not adequately capture the non-linear relationships and interactions among laboratory-derived sprint tes...

Automated Scan Region Classification and Patient-specific Dose Modeling for Enhanced Dose Management in Computed Tomography.

OBJECTIVES: Effective dose management in computed tomography is impeded by 2 key operational challenges: error-prone manual protocol mapping and the h...

Computational validation of a wearable biomechanical sensor network framework for real-time fatigue monitoring and performance prediction in gymnastic training.

This study introduces a simulation-based wearable biomechanical sensor network framework intended to support real-time fatigue monitoring and performa...

Circulating microRNA profiles associated with tick bite and debilitating symptom complexes attributed to ticks (DSCATT).

Tick bites in Australia are associated with a poorly understood syndrome known as Debilitating Symptom Complexes Attributed to Ticks (DSCATT), however...

Engagement Patterns with an AI Health Coach for Systemic Sclerosis Self-Management: A Mixed Methods Study.

OBJECTIVE: To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self-management and identify patterns asso...

Dynamic models of occupational fatigue: a systematic review for risk management advancement.

BACKGROUND: Occupational fatigue is a major safety and health risk across work sectors. Because fatigue accumulates and fluctuates over time, effectiv...

Deep learning of pretreatment ascites cytopathology for platinum-resistance risk stratification in advanced epithelial ovarian cancer.

BACKGROUND: Platinum resistance is a major determinant of poor outcome in advanced epithelial ovarian cancer, yet reliable predictors available before...

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...

Molecular, cellular and network mapping of brain structural deviations in patients with Post-COVID19 syndrome.

Post-COVID-19 syndrome encompasses persistent cognitive, neurological, and psychiatric symptoms following SARS-CoV-2 infection, profoundly affecting g...

Machine learning models to predict ICU admission of patients with COPD and depression: A retrospective cohort study.

This study aimed to develop and validate a machine learning (ML)-based predictive model to identify risk factors associated with intensive care unit (...

Annotated digital image correlation displacement fields from fatigue crack growth experiments on aluminium alloys.

We present a curated dataset of planar displacement fields from eight fatigue crack growth experiments obtained via full-field digital image correlati...

Rational design of an optimized ferritin nanoparticle vaccine targeting both SARS-CoV-2 and MERS-CoV.

BACKGROUND: Coronaviruses including SARS-CoV-2 and MERS-CoV remain threats to global health. Ferritin nanoparticle-based vaccines are promising platfo...

Integrative Bioinformatics and Experimental Validation Identify LOX as a Glycolysis-Related Biomarker in Myocardial Ischemia-Reperfusion Injury.

Reprogramming of glycolytic metabolism plays a critical role in the pathogenesis of myocardial ischemia-reperfusion injury (MIRI). Although transient ...

EEG Connectivity Signatures in Active vs. Passive Mental Fatigue Settings.

In real-world occupational settings, mental fatigue commonly emerges from the combination of sleep deprivation with prolonged cognitive and physical w...