Anemia

Distinguishing post-COVID from long-COVID in adults: Development and validation of a biomarker signature using targeted proteomics and machine learning in a cross-sectional observational study.

BACKGROUND: COVID-19 can have diverse clinical manifestations, ranging from asymptomatic infection to critical illness with multiorgan involvement. While many patients recover fully, others develop long-COVID, a heterogeneous condition marked by persistent symptoms beyond the acute phase. The immunological pathomechanisms between long-COVID and other post-acute recovery states remain unclear. OBJE...

Enhancing the efficacy of Salvia miltiorrhiza and Ligusticum chuanxiong in the treatment of coronary heart disease: The value of poorly soluble components and nanocrystal self-stabilized solid emulsions.

BACKGROUND: The Salvia miltiorrhiza-Ligusticum chuanxiong herb pair is a classic combination in traditional Chinese medicine (TCM) formulation for coronary heart disease (CHD). However, currently marketed preparations primarily retain water-soluble components, while poorly water-soluble yet pharmacologically critical constituents (e.g., tanshinones, Ligusticum chuanxiong oil) are either excluded o...

msCNN-PLM-FAD: Enhanced predicting FAD binding sites by using protein language representation combined with multiple separable windows convolutional neural networks.

The FAD binding sites classification problem is crucial because it is directly related to many diseases, such as flavoprotein-associated diseases, dev...

Multi-Scale Mapping of Gene Expression from Whole-slide Images for Identifying Phenotype-Associated Subpopulations.

Discovery of phenotype-associated subpopulations is critical for targeted therapies and prognostic biomarker discovery, which requires multi-scale gen...

Vascularisation in 3D bioprinted models: emerging solutions engineering functional tissues and tumour models.

Three-dimensional (3D) bioprinting enables the fabrication of tissues with controlled architecture and cell composition, yet the formation of mature a...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individual's brain age, allowing calculation of the brain a...

Predicting low oxygen in patients with acute COVID-19 infection isolating at home: a clinical prediction model.

RATIONALE: Identifying patients who could be safely managed at home versus those needing hospitalisation was a particular concern during early COVID-1...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individual's brain age, allowing calculation of the brain a...

Designing an explainable algorithm based on XGBoost and genetic algorithm for predicting hospitalization needs of COVID-19 patients.

Timely identification of COVID-19 outpatients who are at risk of hospitalization is critical for preventing clinical deterioration and optimizing heal...

Artificial Intelligence-Based Analysis of Central Nervous System Vasculopathy in Pediatric Sickle Cell Anemia.

In children with sickle cell anemia (SCA), central nervous system (CNS) complications such as chronic vasculopathy, silent cerebral infarcts, and over...

Emerging trends and converging evidence in tumor evolution: A comprehensive review.

BACKGROUND: Tumor evolution is a spatiotemporal dynamic process orchestrated by the interplay of genetic mutations, epigenetic reprogramming, and bidi...

Combining multimodal fatigue fracture surface images for analysis with a CNN.

This work uses three different modalities, namely SEM, BSE and scanning white light interference (SWLI) to image fatigue fracture surfaces of Ti-6Al-4...

Identification of a Potential Biomarker PDGFRA for Endometriosis Based on Comprehensive Analysis of Multiple Omics Data.

Endometriosis (EMs) is a common chronic inflammatory gynecological disorder. But the exact pathogenetic mechanism of the disease is not clear, with so...

Development and Validation of a Frailty Risk Prediction Model for Preoperative Non-Small-Cell Lung Cancer Patients: A Cross-Sectional Study.

PURPOSE: Frailty is increasingly recognized as a predictor of poor surgical outcomes, yet its preoperative assessment in patients with non-small-cell ...

Novel Systemic Associations of Idiopathic Epiretinal Membrane Identified via Machine Learning.

PURPOSE: To discover novel systemic associations that may lead to idiopathic epiretinal membrane (iERM) using interpretable machine learning models. D...

Longitudinal brain-age predictions comprising long-duration spaceflight missions.

Our study investigates the effects of long-duration spaceflight on brain aging in spacefarers using structural MRI and machine learning models. Pre-, ...

Use of artificial intelligence and machine learning for the management of fibromyalgia: a scoping review.

BACKGROUND: Fibromyalgia (FM) is a complex and multifactorial syndrome characterized by widespread pain, fatigue, cognitive impairment, and other syst...

Bi-directional YOLOv10 with average convolution for brain tumor detection in MRI.

Medical professionals rely on MRI scans to evaluate brain tumors, a task prone to fatigue and subjective interpretation. This study enhances the YOLOv...

Longitudinal modeling of Post-COVID-19 condition over three years: A machine learning approach using clinical, neuropsychological, and fluid markers.

Post-COVID-19 condition (PCC) manifests with prolonged, heterogeneous symptoms challenging both, diagnosis and therapeutic management. This three-year...

Prevalence and factors associated with suicidal ideation based on the Malaysia National Health and Morbidity Survey: A machine learning analysis.

BACKGROUND: This study estimated the prevalence of past-two-week suicidal ideation and examined its demographic, clinical, and health-related correlat...