Hematology

O blood usage trends in the pediatric population 2015-2019: A multi-institutional analysis.

BACKGROUND: In 2019, AABB released the bulletin "Recommendations on the Use of Group O Red Blood Cel...

Gold nanorods as multidimensional optical nanomaterials: machine learning-enhanced quantitative fingerprinting of proteins for diagnostic applications.

The rapid and precise quantification and identification of proteins as key diagnostic biomarkers hol...

The interpretable machine learning model for depression associated with heavy metals via EMR mining method.

Limited research exists on the association between depression and heavy metal exposure. This study a...

Addressing Hemolysis-Induced Loss of Sensitivity in Lateral Flow Assays of Blood Samples with Platinum-Coated Gold Nanoparticles and Machine Learning.

Gold nanoparticles (GNPs), which appear red, are widely used as labels in lateral flow assays (LFAs)...

A prospective study for the examination of peripheral blood smear samples in pediatric population using artificial intelligence.

BACKGROUND/AIM: Peripheral blood smear (PBS) and bone marrow aspiration are gold standards of manual...

Discovery and characterization of novel FAK inhibitors for breast cancer therapy via hybrid virtual screening, biological evaluation and molecular dynamics simulations.

Focal adhesion kinase (FAK) is a critical drug target implicated in various disease pathways, includ...

Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines.

OBJECTIVE: Bloodstream infection (BSI) is a significant cause of mortality in patients with hematolo...

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mor...

Nutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach.

Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of ...

Traumatic brain injury: Bridging pathophysiological insights and precision treatment strategies.

Blood-brain barrier disruption and the neuroinflammatory response are significant pathological featu...

Machine learning prediction of preterm birth in women under 35 using routine biomarkers in a retrospective cohort study.

Preterm birth (PTB), defined as delivery before 37 weeks, affects 15 million infants annually, accou...

Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes.

Continuous high-resolution imaging of the disease-mediating blood stages of the human malaria parasi...

Prediction model of gastrointestinal tumor malignancy based on coagulation indicators such as TEG and neural networks.

OBJECTIVES: Accurate determination of gastrointestinal tumor malignancy is a crucial focus of clinic...

AI-Derived Blood Biomarkers for Ovarian Cancer Diagnosis: Systematic Review and Meta-Analysis.

BACKGROUND: Emerging evidence underscores the potential application of artificial intelligence (AI) ...

Development and validation of a machine learning model to predict hemostatic intervention in patients with acute upper gastrointestinal bleeding.

BACKGROUND: Acute upper gastrointestinal bleeding (UGIB) is common in clinical practice and has a wi...

Machine Learning-Based VO Estimation Using a Wearable Multiwavelength Photoplethysmography Device.

The rate of oxygen consumption, which is measured as the volume of oxygen consumed per mass per minu...

Development of an artificial intelligence-enhanced warfarin interaction checker platform.

Warfarin is a common anticoagulant drug for thrombo-prophylaxis in stroke and venous thromboembolism...

Deciphering the molecular fingerprint of haemoglobin in lung cancer: A new strategy for early diagnosis using two-trace two-dimensional correlation near infrared spectroscopy (2T2D-NIRS) and machine learning techniques.

Lung cancer remains one of the deadliest malignancies worldwide, highlighting the need for highly se...

Explainable SHAP-XGBoost models for pressure injuries among patients requiring with mechanical ventilation in intensive care unit.

pressure injuries are significant concern for ICU patients on mechanical ventilation. Early predicti...

Anticoagulation colloidal microrobots based on heparin-mimicking polymers.

Coagulation within blood vessels is a major cause of cardiovascular disease and global mortality, hi...

Precision Risk Stratification in Atrial Fibrillation: Evaluating Machine Learning Models for Bleeding Prediction and Clinical Integration.