Hematology

Low vitamin D status and cardiometabolic trait clustering in a primary-care adult cohort: association analysis and exploratory explainable machine-learning classification.

BACKGROUND: Low serum 25-hydroxyvitamin D (25(OH)D) commonly co-exists with obesity and adverse cardiometabolic traits. However, its cross-sectional association with dyslipidaemia, body composition and glycaemic markers in primary-care adults remains incompletely characterised. This study examined these associations as the primary objective and, as a secondary exploratory objective, assessed wheth...

Precision Medicine for Anticoagulation Strategies in the Cath Lab: Part 2.

PURPOSE OF REVIEW: Intraprocedural anticoagulation during percutaneous coronary intervention (PCI) remains particularly challenging in high-risk and underrepresented populations, where the balance between thrombotic and bleeding risk is complex and often unpredictable. This review summarizes contemporary evidence and remaining knowledge gaps regarding anticoagulant selection, dosing, and monitorin...

Differentiating septic arthritis from non-infectious inflammatory causes of acute monoarticular arthritis in children: A machine learning approach based on routine laboratory tests.

OBJECTIVE: Acute monoarthritis in children poses a diagnostic challenge, particularly in distinguishing septic arthritis from non-infectious inflammat...

Prospective Validation of Multi-week Inpatient Census Forecasting for Pediatric HSCT and Cellular Therapy.

BACKGROUND: Accurate inpatient census forecasting is important for cell therapy and blood and marrow transplantation (BMT) programs because bed capaci...

Development and validation of an interpretable machine learning model for predicting in-hospital mortality among critically ill patients with liver cirrhosis.

This study aimed to develop and validate an interpretable machine learning model for early prediction of in-hospital mortality in critically ill patie...

The future of pediatric gene therapy: CRISPR-Cas9, AI, and personalized medicine.

The future of pediatric gene therapy is being fundamentally reshaped by the convergence of CRISPR-Cas9 genome editing, artificial intelligence (AI), a...

Integrating multiple hematologic inflammatory indices into a principal component analysis-derived inflammatory burden score for coronary artery disease.

BACKGROUND: Complete blood count-derived inflammatory indices have been associated with coronary artery disease (CAD), but their substantial overlap m...

Detection of malaria infection from parasite-free blood smears.

Malaria affects almost 263 million people worldwide, most of whom live in sub-Saharan countries. In a strategy to reduce malaria-related mortality and...

Development and validation of a routine blood test-based model to predict in-hospital postoperative pulmonary infection in older patients with hip fracture.

BACKGROUND: Postoperative pulmonary infection (PPI) is a common and serious complication in older adults undergoing hip fracture surgery, leading to p...

Establishment of a Multimodal Prognostic Prediction Model for Multiple Myeloma Patients Based on Radiomics and Clinical Features: A Retrospective Cohort Study.

OBJECTIVE: We aimed to develop a survival prediction system integrating radiomics and clinical features for newly diagnosed multiple myeloma (MM), and...

Using Artificial Intelligence to Identify Patterns and Predictors of Adverse Drug Reactions in Cardiovascular Patients: A Comprehensive Narrative Review.

Artificial intelligence (AI) has emerged as a transformative tool for improving the detection, prediction, and prevention of adverse drug reactions (A...

A machine learning approach to non-invasive prediction of hepatic decompensation in compensated advanced chronic liver disease: the CIRI model.

BACKGROUND & AIMS: Hepatic venous pressure gradient (HVPG) is the gold standard for assessment of prognosis in compensated advanced chronic liver dise...

Personalised approach to hypertension treatment: protocol for the HYPERMARKER randomised controlled trial.

INTRODUCTION: Blood pressure treatment response is variable in individual patients, and the choice of medical therapy is often dependent on clinician ...

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.

BASG-Net: a background-aware spatial gating network for cervical cell segmentation in pap smear images.

The precise segmentation of cervical cell images is regarded as a fundamental prerequisite for the implementation of computer-aided cervical cancer sc...

Acute kidney injury severity in ICU patients: Developing and evaluating a data-driven analysis of clinical covariates using machine learning.

BACKGROUND: Acute kidney injury remains a major cause of morbidity and mortality in critically ill patients. Existing classification systems rely on s...

Multistage microrobots with pH-responsive release of platelet membrane-coated nanoparticles.

Targeted drug delivery in the gastrointestinal tract remains challenging because therapeutics must overcome multiple hierarchical barriers before reac...

Biomarkers in predicting mortality in hemodialysis patients: recent advances.

Patients undergoing maintenance hemodialysis face annual mortality rates of 15-27%, with cardiovascular causes accounting for more than half of all de...

Non-invasive arterial blood pressure waveform generation in critically ill patients: A sensor-based deep learning approach.

Continuous monitoring of Arterial Blood Pressure (ABP) in critically ill patients requires invasive arterial catheterization, which carries risks of t...

Decoding the Partitioning Behavior of Poly- and Perfluoroalkyl Substances: Insights from Human Liver and Blood Biomonitoring with Machine Learning.

Perfluoroalkyl substances (PFASs) are known for their tendency to accumulate in the human liver, potentially causing hepatotoxic effects. However, the...