Hematology

A machine learning model for accurate prediction of CMV end-organ disease.

BACKGROUND: Cytomegalovirus (CMV) End-Organ Disease (EOD) remains a significant complication in immunocompromised individuals, particularly transplant recipients and patients undergoing chemotherapy. Accurate prediction of CMV EOD is essential for timely intervention but remains challenging using traditional methods. OBJECTIVE: This study aimed to evaluate the diagnostic performance of machine lea...

Real-world evaluation of large language models in detecting drug-related problems: A clinical pharmacist-AI concordance study in hematology care.

IntroductionLarge language models (LLMs) offer potential as clinical decision support systems (CDSS) for detecting drug-related problems (DRPs), yet their real-world performance compared to clinical pharmacists (CPs) remains unclear, especially in complex hematology care. We aimed to evaluate the concordance between a clinical pharmacist and three LLMs in identifying DRPs within a Bone Marrow Tran...

Prehospital Blood Collection for High Sensitivity Cardiac Troponin Measurement in Patients with Acute Chest Pain.

OBJECTIVES: High sensitivity cardiac troponin (hs-cTn) measures are used in the emergency department (ED) to evaluate patients with acute chest pain. ...

Advances in the postoperative care of the liver transplant recipient.

PURPOSE OF REVIEW: Survival rates following liver transplantation now exceed 90% at one year. However, the patient group undergoing liver transplantat...

Early individualized risk prediction using clinical data for children during the febrile phase of dengue in outpatient settings in Vietnam and Thailand.

Dengue severity prediction models are usually developed using hospitalized patient data, but triage and hospital admission are mainly evaluated in out...

Spectral CT-derived extracellular volume fraction for pathological characterization and noninvasive T staging in colon cancer.

OBJECTIVES: To investigate the association between the extracellular volume fraction (ECV) quantified by spectral CT and multiparameter pathological f...

Classification of twinkling artifacts and blood flow for in vivo detection of breast microcalcifications.

While mammography is the standard modality for detecting microcalcifications (MCs), their real-time detection with ultrasound imaging can be invaluabl...

Development and validation of interpretable machine learning models for predicting long-term functional outcomes in elderly patients with aneurysmal subarachnoid hemorrhage.

BACKGROUND: Accurate prognostication in elderly patients with aneurysmal subarachnoid hemorrhage (aSAH) remains challenging due to high morbidity and ...

Artificial intelligence and machine learning for precision warfarin dosing: a comprehensive narrative review.

BACKGROUND: Warfarin remains one of the most widely used anticoagulants; however, its narrow therapeutic index means that even small dosing deviations...

Interpretable deep learning model of circulating genomics for quantitative survival prediction in advanced non-small cell lung cancer.

PURPOSE: Accurate quantitative survival prediction in advanced non-small cell lung cancer (NSCLC) remains an unmet clinical need. While liquid biopsy ...

Deep learning-integrated multilayer thermal gradient sensing platform for real-time blood flow monitoring.

Blood flow monitoring is fundamental for assessing cardiovascular health and identifying vascular complications. Traditional Doppler ultrasound method...

Predictors of Glycemic Response to Sulfonylurea Therapy in Type 2 Diabetes Over 12 Months: Comparative Analysis of Linear Regression and Machine Learning Models.

BACKGROUND: Sulfonylureas are commonly prescribed for managing type 2 diabetes, yet treatment responses vary significantly among individuals. Although...

A Large-Scale Peripheral Blood Cell Dataset for Automated Hematological Analysis.

White blood cell classification is fundamental to hematological diagnosis, yet existing datasets are limited in scale and class diversity. We present ...

Data-driven predictive modeling for massive intraoperative blood loss during living donor liver transplantation: Integrating machine learning techniques.

BACKGROUND: Massive intraoperative bleeding (IBL) in liver transplantation (LT) poses serious risks and strains healthcare resources necessitating bet...

Predictive value of hemoglobin-to-red cell distribution width ratio for mortality in new-onset atrial fibrillation after cardiac surgery a machine learning study based on the MIMIC-IV database.

Machine learning-assisted optimization of a terahertz photonic metamaterial absorber for blood cancer detection.

Blood cancer originates in the bone marrow and disrupts the body's normal hematopoietic processes. The rapid progression of this disease highlights th...

Ultrasound-guided microwave ablation for breast tumors: current status and future perspectives.

Ultrasound (US)-guided microwave ablation (MWA) has emerged as a promising minimally invasive therapy for both benign and malignant breast tumors. Thi...

Single-cell Transcriptomic Profiling Reveals Diagnostic of T Cell-platelet Aggregates in Peripheral Blood for Coronary Vulnerable Plaques.

Acute coronary syndrome, driven by vulnerable plaque (VP) instability, is a major cause of cardiovascular mortality. Current diagnostic methods for VP...

Artificial intelligence risk stratification from dynamic digital subtraction angiography radiomics predicts pulmonary embolism and associates with clinical outcomes in deep vein thrombosis: A retrospective cohort study.

OBJECTIVE: Current risk stratification for lower extremity deep vein thrombosis remains limited, often failing to identify high-risk patients for impe...

Study design for an emulated trial of a 2 arm, parallel, stratified, adaptive, RCT of CABG versus PCI in people requiring myocardial revascularization at high risk (High-Risk REVASC).

AIM: This study aims to use routinely collected health data and trial emulation methodology to inform the design of a pragmatic randomized controlled ...