Hematology

Experimental evaluation of deep learning method in reticulocyte enumeration in peripheral blood.

INTRODUCTION: Reticulocytes (RET) are immature red blood cells, and RET enumeration in peripheral blood has important clinical value in diagnosis, treatment efficacy observation, and prognosis of anemic diseases. For RET enumeration, flow cytometric reference method has shown to be more precise than the manual method by light microscopy. However, flow cytometric method generates occasionally spuri...

Robot-assisted laparoscopic hysterectomy for endometrial cancer in a patient with Herlyn-Werner-Wunderlich syndrome.

Herlyn-Werner-Wunderlich syndrome, a rare Mullerian duct anomaly, includes a triad of uterine didelphys, obstructed haemivagina and ipsilateral renal agenesis. A 58-year-old woman with Herlyn-Werner-Wunderlich syndrome, reported of recurrent genital bleeding for 9 years, was finally diagnosed with endometrial cancer. She had a history of vaginal septum resection and nephrectomy of atrophic right k...

A CNN-based unified framework utilizing projection loss in unison with label noise handling for multiple Myeloma cancer diagnosis.

Multiple Myeloma (MM) is a malignancy of plasma cells. Similar to other forms of cancer, it demands prompt diagnosis for reducing the risk of mortalit...

Red blood cell phenotyping from 3D confocal images using artificial neural networks.

The investigation of cell shapes mostly relies on the manual classification of 2D images, causing a subjective and time consuming evaluation based on ...

Two-step machine learning method for the rapid analysis of microvascular flow in intravital video microscopy.

Microvascular blood flow is crucial for tissue and organ function and is often severely affected by diseases. Therefore, investigating the microvascul...

Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears.

Computer-assisted algorithms have become a mainstay of biomedical applications to improve accuracy and reproducibility of repetitive tasks like manual...

In Vitro Measurements of Shear-Mediated Platelet Adhesion Kinematics as Analyzed through Machine Learning.

Platelet adhesion to blood vessel walls in shear flow is essential to initiating the blood coagulation cascade and prompting clot formation in vascula...

Validation of a machine learning approach using FIB-4 and APRI scores assessed by the metavir scoring system: A cohort study.

BACKGROUND AND STUDY AIM: The study aim was to improve and validate the accuracy of the fibrosis-4 (FIB-4) and aspartate aminotransferase-to-platelet ...

Predicting mean ribosome load for 5'UTR of any length using deep learning.

The 5' untranslated region plays a key role in regulating mRNA translation and consequently protein abundance. Therefore, accurate modeling of 5'UTR r...

Detecting cells rotations for increasing the robustness of cell sizing by impedance measurements, with or without machine learning.

The Coulter principle is a widespread technique for sizing red blood cells (RBCs) in hematological analyzers. It is based on the monitoring of the ele...

Quantification of Blood Flow Velocity in the Human Conjunctival Microvessels Using Deep Learning-Based Stabilization Algorithm.

The quantification of blood flow velocity in the human conjunctiva is clinically essential for assessing microvascular hemodynamics. Since the conjunc...

Spatial light interference microscopy: principle and applications to biomedicine.

In this paper, we review spatial light interference microscopy (SLIM), a common-path, phase-shifting interferometer, built onto a phase-contrast micro...

Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains diff...

Recent progress of robotic head and neck surgery using a flexible single port robotic system.

We performed robotic neck surgery through a transoral or retroauricular approach (RA) using the DaVinci SP and analyzed our experiences to evaluate th...

Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.

IMPORTANCE: Anticipating the risk of gastrointestinal bleeding (GIB) when initiating antithrombotic treatment (oral antiplatelets or anticoagulants) i...

Diagnosis of Leukaemia in Blood Slides Based on a Fine-Tuned and Highly Generalisable Deep Learning Model.

Leukaemia is a dysfunction that affects the production of white blood cells in the bone marrow. Young cells are abnormally produced, replacing normal ...

Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit.

Acute gastrointestinal bleeding is the most common gastrointestinal cause for hospitalization. For high-risk patients requiring intensive care unit st...

Using CNN and HHT to Predict Blood Pressure Level Based on Photoplethysmography and Its Derivatives.

According to the WTO, there were 1.13 billion hypertension patients worldwide in 2015. The WTO encouraged people to check the blood pressure regularly...

Comparison of plasma neutrophil gelatinase-associated lipocalin (NGAL) levels after robot-assisted laparoscopic and retropubic radical prostatectomy: an observational study.

BACKGROUND AND OBJECTIVES: Patients undergoing radical prostatectomy are at increased risk of Acute Kidney Injury (AKI) because of intraoperative blee...

Machine learning-based analysis of alveolar and vascular injury in SARS-CoV-2 acute respiratory failure.

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pneumopathy is characterized by a complex clinical picture and heterogeneous pathological...