Hematology

An inflammatory biomarker panel for prediabetes classification using interpretable machine learning.

OBJECTIVE: Prediabetes is a silent condition that often goes undetected. However, timely interventions could prevent its progression to type 2 diabetes. Traditional glycemic markers, such as hemoglobin A1c (HbA1c), have limitations, creating a need for new diagnostic biomarkers. In this study, our objective was to develop an interpretable machine learning model using biomarkers related to oxidativ...

Utilizing stimulation-evoked hemodynamic activity to predict antidepressant response to intermittent theta-burst stimulation in adults with major depression.

BACKGROUND: The instantaneous neural response to prefrontal theta burst stimulation (TBS) may serve as predictive marker for antidepressant treatment success. This study aimed to (1) assess whether baseline theta burst stimulation (TBS)-induced prefrontal hemodynamic responses can predict treatment outcome of four weeks of TBS in adults with major depressive disorder (MDD); (2) assess the test-ret...

Machine learning for predicting macrophage activation syndrome in adult patients with Still's disease.

BACKGROUND: Macrophage activation syndrome (MAS) secondary to Still's disease is a potentially fatal complication, associated with mortality rates exc...

Association of inflammatory biomarkers during pregnancy and the postpartum period with the risk of postpartum anxiety symptoms.

BACKGROUND: Inflammation is pivotal in psychiatric pathophysiology, yet evidence linking inflammatory biomarkers to postpartum anxiety (PPA) remains l...

Routine blood tests and machine learning identify complications in high myopia.

High myopia can lead to cataract, glaucoma, retinal detachment, choroidal neovascularisation, and macular degeneration, causing irreversible vision lo...

Influence of blood transfusion on outcomes in patients with gastric cancer.

Chen et al's research provides valuable data supporting the cautious use of transfusions during gastric cancer surgery. However, to interpret causalit...

Decoding the Blood-Brain Barrier: Innovative and Scalable Open-Source Machine Learning Model for Drug Permeability.

INTRODUCTION: The permeability of the blood-brain barrier (BBB) is an important property for potential drugs. Various in vitro and in vivo methods hav...

A Machine learning pipeline to investigate tissue ingrowth in cerebral aneurysms using preclinical animal models.

Cerebral aneurysm is a life-threatening condition characterized by the formation of a saccular bulge in brain blood vessels, which can rupture and lea...

Artificial intelligence-based chest X-ray (AI-CXR) and hematology parameters to predict mortality and intubation events In COVID-19 patients at the second-referral hospital in Indonesia.

Clustering of cardiovascular risk factors and their association with socio-demographic and lifestyle factors in middle-aged and older adults in rural northeast South Africa: Findings from HAALSI.

OBJECTIVES: This study examined patterns of clustering of intermediate risk factors for Cardiovascular diseases (CVDs) in a rural South African popula...

Artificial intelligence-based analysis of thrombotic and infectious risk factors in peripherally inserted central catheters (PICCs).

INTRODUCTION: Peripherally inserted central catheters (PICCs) are increasingly used in France for prolonged intravenous therapies such as chemotherapy...

Genetic and clinical determinants of tacrolimus accumulation in early liver transplantation: evidence for a combined genotype-antibiotic effect.

BACKGROUND: Tacrolimus is a first-line immunosuppressant essential for preventing graft rejection after liver transplantation, but its narrow therapeu...

A complete blood count-based machine learning model for rapid differentiation of aplastic anemia, immune thrombocytopenia, and myelodysplastic syndromes in routine clinical practice.

BACKGROUND: Accurate differentiation of common hematologic disorders remains challenging in routine clinical practice and often requires invasive diag...

Rapid Proteome-Wide Discovery of Protein-Protein Interactions With ppIRIS.

Protein-protein interactions (PPIs) are central to cellular processes and host-pathogen dynamics across all domains of life, yet comprehensive interac...

Complete Blood Count-Derived Inflammation Indices to Predict 3-Year All-Cause Mortality in Patients With Diabetes and Acute Myocardial Infarction in Critical Care: Retrospective Cohort Study With Single-Center External Validation.

BACKGROUND: Inflammation plays a pivotal role in the progression of diabetes and its cardiovascular complications, particularly acute myocardial infar...

Exploratory analysis of the associations of the brain age gap with cognitive function and amyloid-β accumulation: participants selection based on metabolic and physiological blood markers.

The brain age gap (BAG) is defined as the difference between brain age estimated from MRI using artificial intelligence and chronological age, and has...

Machine learning-based diagnostic modeling for differentiating lymphoid hyperplasia from acute appendicitis using laboratory biomarkers.

BACKGROUND: This study aimed to assess the diagnostic ability of routine laboratory biomarkers and develop machine learning (ML) models to improve dif...

Integrated reiterative pipeline for rapid epitope-based pan-alphavirus vaccines.

The vast diversity of the virosphere underscores the need for rapid, adaptable vaccine development infrastructures. Arthropod-borne zoonotic alphaviru...

Establishing a relationship between iron-based blood measures and structural brain changes using neural networks in UK Biobank.

BACKGROUND: Disturbance of iron homeostasis in both the brain and blood is linked to cognitive impairment and neurodegenerative diseases. Investigatio...

Towards fully automated synthetic ECV quantification: an open-access machine learning-based approach for fast blood draw-free CMR.

Extracellular volume (ECV) quantification involves time-consuming multi-step post-processing and a blood draw for hematocrit analysis. This study aime...