Hematology

Percutaneous coronary intervention in high bleeding risk patients: a review of contemporary management strategies.

INTRODUCTION: High bleeding risk (HBR) affects over one-third of patients undergoing percutaneous coronary intervention (PCI) and is associated with elevated mortality due to both hemorrhagic and ischemic complications. Optimizing management of these patients remains a critical challenge in contemporary interventional cardiology. AREAS COVERED: This review summarizes advances in bleeding risk asse...

Advances in Electrocardiogram-Based Non-Invasive Blood Glucose Monitoring Technology.

Blood glucose monitoring is fundamental to diabetes management, yet traditional invasive methods are limited by patient discomfort and infection risks. In recent years, electrocardiogram (ECG), a conventional tool for cardiovascular assessment, has gained attention as a prospective method for non-invasive blood glucose monitoring. The underlying principle is that glycemic fluctuations can modulate...

Interpretable Clinical-Radiomics Model for Prediction of Blood Stasis and Left Atrial Appendage Thrombus.

BACKGROUND: The left atrial (LA) morphological profile, anatomically contiguous with the left atrial appendage (LAA), exhibits hemodynamic properties ...

Development and Validation of a Machine Learning Model for Predicting 3-Year Overall Survival After Transjugular Intrahepatic Portosystemic Shunt: A Retrospective Multicenter Study.

BACKGROUND AND AIMS: Predicting overall survival (OS) in cirrhotic patients undergoing transjugular intrahepatic portosystemic shunt (TIPS) remains ch...

White blood cell classification using custom deep neural network and visualizing features of the images using heatmaps.

Blood count is a key method for diagnosing diseases by analyzing blood cell images using advanced equipment. Traditionally, this process involves inva...

Past, present and future perspectives of traumatic brain injury.

Despite extensive research, traumatic brain injury (TBI) imposes significant mortality and morbidity burden globally. This narrative review provides a...

Development of machine learning-based predictive models for seroma formation after transabdominal preperitoneal inguinal hernia repair.

BACKGROUND: Inguinal hernia repair, particularly transabdominal preperitoneal (TAPP) repair, is a common surgical procedure. However, seroma formation...

Graph Machine Learning Can Estimate Drug Concentrations in Whole Blood from Forensic Screening Results.

LC-HRMS is widely used in forensic toxicology for broad-scope screening. When a newly emerging or rarely encountered compound is tentatively identifie...

Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time.

BACKGROUND: Timely recognition of oral anticoagulant use is critical in acute stroke but is often hampered by impaired consciousness and unavailable m...

Developing a practical machine learning model to predict post implantation syndrome after endovascular aneurysm repair.

BACKGROUND: Post-implantation syndrome (PIS) is recognized as a systemic inflammatory response following endovascular aneurysm repair (EVAR), characte...

Prospective Evaluation of Large Language Model Integration Into a Classical Hematology Case Conference.

Prospective integration of large language model tools into a classical hematology challenging-cases conference was feasible, increased clinician famil...

A review on oxidation pretreatment for mitigating ultrafiltration membrane fouling caused by natural organic matter in water treatment.

Ultrafiltration (UF) is a promising water treatment technology due to its low energy consumption, cost-effectiveness, and efficient removal of microbi...

Noninvasive Detection of Occult yet Significant Liver Pathology in Alanine Aminotransferase-Normal Chronic Hepatitis B: A Multicenter Study.

BACKGROUND: Individuals with chronic hepatitis B (CHB) may harbor occult yet significant liver pathology despite normal alanine aminotransferase (ALT)...

Communicating bad news in oncology and hematology settings: A statistic and Large Language Model for interpreting nurses' difficulties and emotions - CORRIGENDUM.

Unsupervised clustering analysis unravels the role of systemic inflammatory indices in the prognosis of patients with locally advanced cervical cancer treated with chemoradiation.

BACKGROUND AND PURPOSE: This study aimed to predict the treatment outcomes and survival of patients with locally advanced cervical cancer (LACC) recei...

Insulin resistance prediction from wearables and routine blood biomarkers.

Insulin resistance (IR), a primary precursor to type 2 diabetes, is characterized by impaired insulin action in tissues1. However, diagnostic methods ...

LAMB1 regulates COL3A1 and RAC1 expression during subchorionic hemorrhage progression.

BACKGROUND: Subchorionic hemorrhage (SCH) is characterized by a fluid-filled hypoechoic area in early pregnancy. This study investigates how laminin s...

Machine Learning in the ICU: Predicting Mortality in Patients with Carbapenem-Resistant Gram-Negative Bacilli Bloodstream Infections.

Background and ObjectiveMultidrug and carbapenem resistant gram-negative bacilli bloodstream infections cause high mortality in intensive care units (...

Machine Learning Prediction of Progression to Dialysis in Patients With Polycystic Kidney Disease: Population-Based Retrospective Cohort Study.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD), characterized by progressive cyst growth and renal decline, is the leading genetic c...

Response to: Correspondence on "Evaluation of the impact of NOAC underdosing and exploration of bleeding risk factors in elderly patients with atrial fibrillation: artificial intelligence-based approach" by Protzenko et al.