Hematology

Machine learning predicts stem cell transplant response in severe scleroderma.

OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSCT) compared with cyclophosphamide (CYC). We mapped PBC (peripheral blood cell) samples from the SCOT clinical trial to scleroderma intrinsic subsets and tested the hypothesis that they predict long-term response to HSCT.

Reverse pseudohyperkalemia is more than leukocytosis: a retrospective study.

BACKGROUND: Hyperkalemia is a potentially life-threatening electrolyte abnormality that often requires urgent treatment. Clinicians should distinguish true hyperkalemia from pseudohyperkalemia and reverse pseudohyperkalemia (RPK). RPK has exclusively been described in case reports of patients with hematologic malignancies (HMs) and extreme leukocytosis [white blood cell (WBC) count >200 × 10/mL].

PCR-detectable DNA exists a short period in the blood of systemic candidiasis murine model.

Invasive candidiasis is a major challenge to clinical medicine today. However, traditional fungal diagnostic techniques and empirical treatments have ...

A rapid white blood cell classification system based on multimode imaging technology.

In order to simplify the complexity of white blood cell classification in existing point-of-care testing (POCT) testing equipment, a white blood cell ...

ALICE: a hybrid AI paradigm with enhanced connectivity and cybersecurity for a serendipitous encounter with circulating hybrid cells.

A fully automated and accurate assay of rare cell phenotypes in densely-packed fluorescently-labeled liquid biopsy images remains elusive. Employing ...

Importance of general adiposity, visceral adiposity and vital signs in predicting blood biomarkers using machine learning.

INTRODUCTION: Blood biomarkers are measured for their ability to characterise physiological and disease states. Much is known about linear relations b...

Objective assessment of stored blood quality by deep learning.

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often as...

Utilization of machine-learning models to accurately predict the risk for critical COVID-19.

Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for deterioration during their hospital stay is essential...

Deep learning-based fetoscopic mosaicking for field-of-view expansion.

PURPOSE: Fetoscopic laser photocoagulation is a minimally invasive surgical procedure used to treat twin-to-twin transfusion syndrome (TTTS), which in...

Numerical simulation of deformed red blood cell by utilizing neural network approach and finite element analysis.

In order to have research on the deformation characteristics and mechanical properties of human red blood cells (RBCs), finite element models of RBC o...

A Proxy for Detecting IUGR Based on Gestational Age Estimation in a Guatemalan Rural Population.

progress of fetal development is normally assessed through manual measurements taken from ultrasound images, requiring relatively expensive equipment...

Assessment of the Effect of Infliximab on Immunomodulation Properties of Mesenchymal Stem Cells .

Mesenchymal stem cells (MSCs) have immunomodulatory traits making them a promising choice in the treatment of inflammatory diseases such as graft-ver...

Long-Term Course of Haemoglobin and Ferritin Values in High-Frequency Donors of Whole Blood and Double Erythrocyte Apheresis.

BACKGROUND: High-intensity donation is a risk factor for iron deficiency in blood donors. Interdonation intervals for whole blood (WB) donation and do...

Endoscopic activity, tissue factor and Crohn's disease: findings in clinical remission patients.

BACKGROUND: As Crohn's disease (CD) is associated with a high risk of thromboembolic events (TE), including patients with subclinical inflammation, we...

Prospective Nonrandomized Comparison Between Open and Robot-Assisted Kidney Transplantation: Analysis of Midterm Functional Outcomes.

To compare short- and midterm outcomes of the first 55 patients undergoing robot-assisted kidney transplant (RAKT) with patients undergoing open kidn...

Application of a new HMW framework derived ANN model for optimization of aquatic dissolved organic matter removal by coagulation.

Removing dissolved organic matter (DOM) with polyaluminium chloride is one of the primary goals of drinking water treatment. In this study, a new HMW ...

Identifying prostate cancer and its clinical risk in asymptomatic men using machine learning of high dimensional peripheral blood flow cytometric natural killer cell subset phenotyping data.

We demonstrate that prostate cancer can be identified by flow cytometric profiling of blood immune cell subsets. Herein, we profiled natural killer (N...

Morphogo: An Automatic Bone Marrow Cell Classification System on Digital Images Analyzed by Artificial Intelligence.

INTRODUCTION: The nucleated-cell differential count on the bone marrow aspirate smears is required for the clinical diagnosis of hematological maligna...

Inexpensive, non-invasive biomarkers predict Alzheimer transition using machine learning analysis of the Alzheimer's Disease Neuroimaging (ADNI) database.

The Alzheimer's Disease Neuroimaging (ADNI) database is an expansive undertaking by government, academia, and industry to pool resources and data on s...

Molecular design of antimicrobial conjugated oligoelectrolytes with enhanced selectivity toward bacterial cells.

A series of cationic conjugated oligoelectrolytes (COEs) was designed to understand how variations in molecular dimensions impact the relative activit...