Hematology

Predicting PPOI secondary to laparoscopic radical resection of rectal cancer combined with lobaplatin hyperthermic intraperitoneal chemotherapy: a multi-center study.

PURPOSE: PPOI is one of the common complications of intraperitoneal hyperthermic chemotherapy during laparoscopic radical resection of rectal cancer, which seriously affects the prognosis of patients. The purpose of this study is to establish a prediction system for PPOI secondary to laparoscopic radical resection of rectal cancer combined with intraperitoneal hyperthermic chemotherapy with lobapl...

Preanalytical Workflow Establishment for Reproducible Clinical Blood-Based Infrared Molecular Fingerprinting.

Standardized preanalytical sample handling is a cornerstone of reliable molecular analytics, particularly where subtle multimolecular differences can drive biological interpretation. In different clinical studies, blood-based samples are often processed using varying workflows, and the influence of individual technical parameters remains poorly quantified. In particular, preanalytical differences ...

Development of an Arterial Carbon Dioxide Estimation Model Using End-Tidal Carbon Dioxide Levels during Surgery in the Pediatric Population.

BACKGROUND: Intraoperative arterial carbon dioxide partial pressure monitoring is essential for pediatric ventilatory management but requires invasive...

Plasma proteomics improves thrombosis prediction in patients with cancer and identifies targetable IL-17-driven endothelial activation.

Thrombosis remains a major cause of morbidity and mortality in patients with cancer. Existing risk models fail to reliably predict venous thromboembol...

Single-cell transcriptomic analysis reveals the T lymphocyte microenvironment and identifies HOPX as a hub gene in membranous nephropathy.

BACKGROUND: Membranous nephropathy (MN) is an autoimmune disease characterized by immune complex deposition and progressive renal function impairment....

Clinical Validation of the MC-80 Digital Morphology Analyzer in Leukocyte Classification: A Large-Scale Comparison With Manual Microscopy.

INTRODUCTION: Although AI-powered digital morphology analyzers are widely used for leukocyte classification, their reliability in detecting clinically...

Evaluating artificial intelligence-generated multiple-choice questions in clinical pathology.

Large language models are increasingly applied in medical education, but their role in clinical pathology remains uncertain. We conducted a prospectiv...

Multimodal Deep Learning for Predicting Deep Vein Thrombosis Risk After Total Knee Arthroplasty: A Clinical Study.

BACKGROUND: Deep vein thrombosis (DVT) following total knee arthroplasty (TKA) remains a major postoperative complication. Conventional risk assessmen...

Predicting coronary artery lesions in Kawasaki disease: a nomogram based on LASSO regression feature selection.

BACKGROUND: Coronary artery lesions (CALs) represent the most serious complications of Kawasaki disease (KD), and the early identification of children...

[Construction and validation of a prognostic prediction model for children-onset initial steroid-resistant nephrotic syndrome].

Objective: To analyze the risk factors for poor prognosis in children with steroid-resistant nephrotic syndrome (SRNS) and to construct and validate a...

An Integrated Rotation-Programmed and Gravity-Driven Microfluidic Platform for Direct Bacterial Detection from Whole Blood.

For the precise molecular detection of bloodstream infection, sample processing is critical, as it involves purifying pathogenic DNA to circumvent the...

Integrative analysis of mortality risk in SFTS using machine learning and genetic approaches.

This study presents a novel approach to predicting mortality risk in patients with severe fever with thrombocytopenia syndrome (SFTS) by integrating m...

Machine learning to identify novel bleeding and residual thromboembolic risks in patients on anticoagulation.

Balancing thromboembolic prevention against bleeding risk remains a key challenge during oral anticoagulant (OAC) therapy. CHA₂DS₂-VASc cannot predict...

Local infection signs at the catheter-insertion site: a large prospective multicentric cohort study.

OBJECTIVES: To describe the epidemiology of local signs at intravascular catheter insertion sites across catheter types and care settings, to compare ...

Global performance of predictive models for dengue severity, hospitalization and mortality: a systematic review and meta-analysis of 146 studies.

OBJECTIVES: Predictive models are increasingly used to support the clinical management of dengue, but their performance varies widely across settings....

Diagnostic performance of discriminant formulas and machine learning models for detecting β-thalassemia trait in Bangladesh.

BACKGROUND: β-thalassemia poses a considerable public health burden in Bangladesh, where a high carrier frequency underlies widespread disease risk. I...

Data subdivision approach enhances machine learning-based mortality prediction in pediatric ICU patients.

OBJECTIVE: To evaluate machine learning-based models for predicting all-cause mortality in pediatric ICU patients using comprehensive biochemical pane...

DinoFlow: Self-supervised pretraining in flow cytometry enables accurate detection of common hematopathological disorders.

Flow cytometry is an essential component of routine hematological lab testing. Many computational methods have been proposed for the analysis of flow ...

Prediction of intensive care unit requirement and in-hospital mortality in Fournier's gangrene: a comparative analysis of conventional statistical and machine learning models.

This study aimed to evaluate the need for intensive care unit (ICU) admission and identify factors associated with in-hospital mortality (IHM) in pati...

Machine learning versus deep learning for screening ischemic stroke among asymptomatic population.

Ischemic stroke puts great health burden in public. However, the diagnosis is based on head CT or MRI scanning. We aim to develop classifier models to...