Hematology

Enhanced predictive performance of artificial intelligence in individualized ovarian stimulation of in vitro fertilization: a retrospective cohort study.

BACKGROUND: Over 2.5 million cycles in vitro fertilization (IVF) are conducted annually, and numbers are expected to rise with the aging population. The controlled ovarian stimulation (COS) process, key to IVF success, is inherently complex. Given advances in artificial intelligence (AI), this study investigated whether a series of AI models can outperform traditional clinical practices in predict...

Hematologic Patterns in Differentiating DRESS From Morbilliform Drug Eruptions: A Preliminary Investigation.

Background: Drug reaction with eosinophilia and systemic symptoms (DRESS) and morbilliform drug eruption (MDE) are 2 distinct drug eruptions that can appear clinically similar at presentation. Given the significant morbidity of DRESS, there is a need for objective markers that can aid in early recognition.Objective: The purpose of this study is to explore the diagnostic potential of routine hemato...

Integrated and Ultrafast Multiomics Sample Preparation Workflow for Screening Biomarker Panel of Platelet Biomolecules for Early Diagnosis of HCC.

Early detection of hepatocellular carcinoma (HCC) remains a persistent worldwide challenge. Owing to its minimal invasiveness, liquid biopsy has emerg...

[Digital transformation in endocrinology/diabetology, pneumology, and hematology/oncology : Where do we stand today-and what lies ahead?].

As in many areas of medicine, increasing digitalisation is also having an impact on everyday practice in internal medicine, entailing both enormous po...

Fusing serum peptidome profiles with clinical variables via machine learning for pulmonary embolism risk assessment.

Pulmonary embolism (PE) remains a life-threatening cardiovascular emergency that requires timely and accurate diagnosis. Current diagnostic strategies...

From innovation to implementation: Addressing the AI adoption gap in cardiac surgery.

BACKGROUND: While artificial intelligence (AI) is advancing rapidly across cardiovascular medicine, its translation into cardiac surgery remains limit...

AI-Enabled Personalization of Semaglutide Therapy in Type 2 Diabetes: Systematic Review With an Integration Framework.

BACKGROUND: Type 2 diabetes mellitus (T2D) is a rapidly growing global health concern requiring innovative treatment methods. Ozempic (semaglutide), a...

Integrating machine learning with SHAP to uncover multi-tissue molecular signatures in Osteoarthritis progression.

Osteoarthritis (OA) is a chronic joint disorder characterized by pain, reduced mobility, and structural degeneration. Despite its complex etiology and...

Characterization of biomarker profiles in patients with coronary artery disease: A prospective coronary computed tomography angiography study.

BACKGROUND AND AIMS: Conventional biomarkers such as low-density lipoprotein (LDL) and high-density lipoprotein may fail to identify patients' risk fo...

Increased Prevalence of Extrathymic Neoplasms in Myasthenia Gravis Patients-A Population-Based, Matched Case-Control Study.

INTRODUCTION/AIMS: Myasthenia gravis (MG) is associated with thymic neoplasms. However, an increased prevalence of extrathymic neoplasms has also been...

Preoperative Risk Score for Mortality Within 3 Years of Elective Aortobifemoral Artery Bypass.

BACKGROUND: The purpose of this study was to create a risk score for mortality within 3 years of elective aortobifemoral artery bypass for aortoiliac ...

Cross-validation strategies under data dependency: An example with anemia prediction in sheep using ocular conjunctiva images.

Computer vision techniques have been increasingly used in livestock farming for tasks such as animal identification and health monitoring, but their p...

A systematic review of machine and deep learning techniques for acute lymphoblastic leukemia diagnosis.

Acute lymphoblastic leukemia (ALL) is a hematological malignancy characterized by the rapid proliferation of immature white blood cells in the bone ma...

Artificial intelligence for venous thromboembolism risk stratification in surgical patients: a systematic review.

Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), is a significant complication in surgical patients. Ar...

Percutaneous nephrostomy guidance by a convolutional-neural-network-based optical coherence tomography endoscope.

Percutaneous nephrostomy is widely used in kidney access surgeries. Despite its prevalence in urological interventions, it presents two operational ch...

Predicting VRE Infection After Liver Transplantation With a Time-Updated Colonization Score.

BACKGROUND: Vancomycin-resistant Enterococcus (VRE) infection is a life-threatening complication after liver transplantation (LT). This study aimed to...

Integrative multi-omics and machine learning identify mitochondrial biomarkers for pathogen-specific sepsis stratification and translational prioritization.

BACKGROUND: Sepsis is a leading cause of critical illness and mortality, yet substantial heterogeneity limits risk stratification and biomarker transl...

Climate predictors of child undernutrition: Insights from a machine learning model.

BACKGROUND: Climate variability is increasingly recognized as a driver of child undernutrition, yet the non-linear relationships between specific clim...

Predictive divergence in machine learning models for clinical mortality risk: A multicohort study of covid-19 patients.

BACKGROUND: Machine learning (ML) algorithms are increasingly used in healthcare to support clinical decision-making. While models with similar overal...

Phenotypic clustering of myocardial infarction complicated by out-of-hospital cardiac arrest using unsupervised machine learning.

BACKGROUND: Patients with myocardial infarction (MI) complicated by out-of-hospital cardiac arrest (OHCA) represent a heterogeneous population with va...