Hematology

Single capture quantitative oblique back-illumination microscopy.

Quantitative oblique back-illumination microscopy (qOBM) has emerged as a powerful technique for lab...

Explainable machine learning predicts mortality in critically ill patients with nonvariceal upper gastrointestinal bleeding: a MIMIC-IV study with external validation.

Characterization of the Sequence of Cytopenia after Total-body Irradiation using Unsupervised Machine Learning.

Hematopoietic acute radiation syndrome (H-ARS) elicits multidimensional effects, as total-body irrad...

Advanced Drug Delivery Strategies for Overcoming Biological Barriers: Tumor Microenvironment and Blood-Brain Barrier.

Therapeutic efficacy for malignancies and neurological disorders is fundamentally restricted by biol...

Chest Computed Tomography-Based Radiomics and Machine Learning for Classifying Mediastinal Lymphadenopathy Caused By Hematologic Malignancies and Metastatic Abdominopelvic Solid Cancers.

PURPOSE: To evaluate the role of chest CT radiomics in classifying mediastinal lymphadenopathy cause...

CHOROIDAL VASCULARITY INDEX, RETINAL VASCULARITY, AND HEMOGLOBIN LEVELS IN PEDIATRIC SICKLE CELL MACULOPATHY.

PURPOSE: To evaluate the choroidal vascularity index (CVI) in pediatric patients with sickle cell di...

A predictive model for significant periodontal disease progression: A large-scale cohort study.

BACKGROUND: The progression of periodontitis is challenging to predict. This study aimed to develop ...

Machine Learning-Driven Prognostic Model Integrating Lymphocyte-to-C-Reactive Protein Ratio and TNM Staging in Gallbladder Cancer.

BACKGROUND: A comprehensive preoperative assessment of the patient's physical condition is crucial f...

Machine Learning in Assessing Intraoperative Blood Loss: A Systematic Review and Meta-Analysis.

AIM: To evaluate the value of machine learning in assessing intraoperative blood loss by comparing a...

Fetal and neonatal alloimmune thrombocytopenia (FNAIT): From reactive transfusion to proactive prevention.

Fetal and neonatal alloimmune thrombocytopenia (FNAIT) is a major cause of severe thrombocytopenia, ...

Predicting infected pancreatic necrosis in acute pancreatitis using machine learning models and feature selection.

Infected pancreatic necrosis (IPN) is a life-threatening complication of acute pancreatitis (AP), an...

A Multi-Omics and machine learning platelet-related prognostic signature in multiple myeloma.

Machine learning estimation of FVIII pharmacokinetic parameters in Chinese children with severe Hemophilia A.

Hemophilia A is a rare inherited bleeding disorder typically managed with coagulation factor VIII (F...

Outcomes with revascularization vs. medical therapy according to plaque burden from coronary computed tomography angiography.

AIMS: We aimed to investigate whether plaque burden from coronary computed tomography angiography (C...

Deep Learning Model to Detect Diabetic Retinopathy in 45° Images Using Ground Truth from Ultra-Widefield Imaging.

PURPOSE: To evaluate the performance of a deep learning (DL) model in classifying diabetic retinopat...

Predicting Nocturnal Hypertension in CKD Through Table-Value Diffusion Model.

BACKGROUND: Ambulatory blood pressure monitoring is indispensable for diagnosing nocturnal hypertens...

msCNN-PLM-FAD: Enhanced predicting FAD binding sites by using protein language representation combined with multiple separable windows convolutional neural networks.

The FAD binding sites classification problem is crucial because it is directly related to many disea...

Deep learning assisted cell electrical signal analysis in impedance cytometry.

In this study, we developed BioFluxNet, a 1D CNN-based algorithm for automated analysis of raw elect...

Ensemble model assisted classification of gastrointestinal bleeding using wireless capsule endoscopy.

Wireless Capsule Endoscopy (WCE) is a useful method for imaging the intestines painlessly and lookin...

Exploring stress and coping among black women in early midlife with elevated blood pressure in a safety-net health system: a qualitative focus group protocol.

INTRODUCTION: Black women in early midlife experience disproportionate exposure to stress and elevat...

Construction of interpretable machine-learning diagnostic models for erectile dysfunction based on routine blood and biochemical detection data.

Despite its high incidence, the diagnosis of erectile dysfunction (ED) is impeded by current diagnos...