Hematology

Inflammatory indices, machine learning and artificial intelligence in tubal ectopic pregnancy management.

OBJECTIVE: To assess the predictive value of hematologic and biochemical inflammatory indices for methotrexate (MTX) treatment outcomes in tubal ectopic pregnancy (TEP) and to develop machine learning (ML) models for individualized risk stratification. MATERIALS AND METHODS: This retrospective cohort included 293 hemodynamically stable TEP patients who were treated with a single dose of MTX betwee...

Automated Gating of CD34+ Cells in Cord Blood: Performance Evaluation of a Machine Learning-Based ISHAGE Protocol.

Precise quantification of cellular subsets is fundamental for qualifying grafts and supporting emerging therapies. CD34+ enumeration in cord blood using the ISHAGE protocol exemplifies the operator variability inherent to manual gating. We evaluated whether a machine-learning approach could provide standardized automated enumeration and reduce variability. A machine-learning-based automatic gating...

Interpretable machine learning for predicting in-hospital bleeding after PCI in patients with diabetes and acute coronary syndrome: a retrospective cohort study.

Machine Learning Prediction of Recurrence in Pediatric Thyroid Cancer: Malignant Endocrine Tumors Cohort Analysis Using XGBoost and SHAP.

CONTEXT: Pediatric differentiated thyroid carcinoma (DTC) often presents with advanced disease but generally has excellent long-term survival. However...

Neoadjuvant Radiation is Causally Linked to Increased Operative Time and Perioperative Blood Transfusion in Pancreatic Ductal Adenocarcinoma.

INTRODUCTION: Blood transfusion in patients undergoing surgical resection for pancreatic ductal adenocarcinoma (PDAC) is associated with worse outcome...

Platelets as immune sensors: monitoring immune dynamics and diagnosing disease states across multiple disorders.

BACKGROUND: Beyond their classical roles in haemostasis and thrombosis, platelets have been recognised as active regulators of immune responses. Howev...

Strategies of AI-Driven CAR-T Cell Therapy Towards Solid Tumours.

Chimeric antigen receptor (CAR)-T cell immunotherapy shows significant success in hematologic malignancies. However, it faces critical challenges in s...

Development of an artificial intelligence platform to improve compliance in periodontal maintenance patients: A proof-of-concept study.

BACKGROUND: The purpose of this study is to report on the development of an artificial intelligence (AI) model designed to improve compliance in perio...

Machine Learning for Predicting Stroke Risk Stratification Using Multiomics Data: Systematic Review.

BACKGROUND: Stroke is a complex, multidimensional disorder influenced by interacting inflammatory, immune, coagulation, endothelial, and metabolic pat...

Screening for Clinically Significant Nephrolithiasis Based on Simple Health Checkup Clinical and Urine Parameters in General Populations: Multicenter Machine Learning Study.

BACKGROUND: Nephrolithiasis affects approximately 15% of the population and often remains undetected in asymptomatic individuals. Current diagnostic a...

Guidelines on optimizing DNA methylation reference panels for cell-type deconvolution.

Accurate cell-type deconvolution is critical for correct interpretation of Epigenome-Wide Association Studies. For all cell-type deconvolution tasks, ...

Bulk and single-cell transcriptomics for identification of potential diagnostic biomarkers associated with pulmonary arterial hypertension and integrated stress response and experimental validation.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a lethal vascular disorder characterized by irreversible remodeling of the pulmonary arteries, bu...

Development of a chemometric-assisted SERS method for simultaneous analysis of HDL and LDL cholesterol in blood serum with silver nanoparticles as substrate.

Cardiovascular diseases (CVD) are becoming a serious threat to human health. These are considered the leading causes of mortality. Abnormal lipid conc...

Novel Systemic Associations of Idiopathic Epiretinal Membrane Identified via Machine Learning.

PURPOSE: To discover novel systemic associations that may lead to idiopathic epiretinal membrane (iERM) using interpretable machine learning models. D...

Lesion-level dual-tracer PET biomarkers predict prognosis in multiple myeloma treated with CXCR4-directed radiopharmaceutical therapy.

BACKGROUND: C-X-C motif chemokine receptor 4 (CXCR4)-directed radiopharmaceutical therapy (RPT) represents a promising option for hematologic malignan...

Identification of molecular diagnostic markers and potential therapeutic drugs for Sjögren's syndrome.

Sjögren's Syndrome (SS) is a long-term autoimmune disorder marked by damage to exocrine glands and irregularities in the immune system. Currently, the...

Hypoglycemia problem-solving ability as a key predictor of severe hypoglycemia: a machine learning approach in adults with type 1 diabetes.

AIMS/INTRODUCTION: Severe hypoglycemia (SH) is a major complication in adults with type 1 diabetes mellitus (T1DM). The multifactorial etiology of T1D...

Identification of clinical phenotypes and disease trajectories in SLE using AI through a natural language processing framework.

OBJECTIVES: Electronic Health Records (EHRs) contain a wealth of unstructured patient data that can be leveraged using Artificial Intelligence (AI). T...

Ethical dilemmas in the use of artificial intelligence in transfusion medicine.

Artificial intelligence (AI) and machine learning (ML) are beginning to enhance key workflows across blood banking (BB) and transfusion medicine (TM),...

Explainable machine learning for risk prediction of acute cardiac tamponade during atrial fibrillation ablation.

Cardiac tamponade is a rare yet catastrophic complication during atrial fibrillation (AF) catheter ablation. Influenced by multiple procedural and pat...