Hematology

Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches.

Flow cytometry nowadays is among the main working instruments in modern biology paving the way for clinics to provide early, quick, and reliable diagnostics of many blood-related diseases. The major problem for clinical applications is the detection of rare pathogenic objects in patient blood. These objects can be circulating tumor cells, very rare during the early stages of cancer development, va...

Regarding: Shung et al: Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding.

RE: Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding.

A neural network approach for real-time particle/cell characterization in microfluidic impedance cytometry.

Microfluidic applications such as active particle sorting or selective enrichment require particle classification techniques that are capable of worki...

Sequential classification system for recognition of malaria infection using peripheral blood cell images.

AIMS: Morphological recognition of red blood cells infected with malaria parasites is an important task in the laboratory practice. Nowadays, there is...

Artificial Intelligence based Models for Screening of Hematologic Malignancies using Cell Population Data.

Cell Population Data (CPD) provides various blood cell parameters that can be used for differential diagnosis. Data analytics using Machine Learning (...

Applications of machine learning for simulations of red blood cells in microfluidic devices.

BACKGROUND: For optimization of microfluidic devices for the analysis of blood samples, it is useful to simulate blood cells as elastic objects in flo...

Vessel and Tension-Free Reconstruction During Robot-Assisted Partial Nephrectomy for Hilar Tumors: "Garland" Technique and Midterm Outcomes.

Robot-assisted partial nephrectomy (RAPN) is increasingly applied to renal hilar tumors. The present study aims to introduce our vessel and tension-f...

A supervised blood vessel segmentation technique for digital Fundus images using Zernike Moment based features.

This paper proposes a new supervised method for blood vessel segmentation using Zernike moment-based shape descriptors. The method implements a pixel ...

An integrated deep learning framework for joint segmentation of blood pool and myocardium.

Simultaneous and automatic segmentation of the blood pool and myocardium is an important precondition for early diagnosis and pre-operative planning i...

Label-Free Leukemia Monitoring by Computer Vision.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. While there are a number of well-recognized prognostic biomarkers at diagnosis...

Machine Learning Analysis for Quantitative Discrimination of Dried Blood Droplets.

One of the most interesting and everyday natural phenomenon is the formation of different patterns after the evaporation of liquid droplets on a solid...

Discovery of Small-Molecule Activators for Glucose-6-Phosphate Dehydrogenase (G6PD) Using Machine Learning Approaches.

Glucose-6-Phosphate Dehydrogenase (G6PD) is a ubiquitous cytoplasmic enzyme converting glucose-6-phosphate into 6-phosphogluconate in the pentose phos...

A proposed health monitoring system using fuzzy inference system.

Due to the busy schedule of every human being in today's world, consciousness towards one's health has become quite alarming. A person suffering from ...

Efficient Prediction of Vitamin B Deficiencies via Machine-Learning Using Routine Blood Test Results in Patients With Intense Psychiatric Episode.

BACKGROUND: Vitamin B deficiency is common worldwide and may lead to psychiatric symptoms; however, vitamin B deficiency epidemiology in patients with...

Efficient Classification of White Blood Cell Leukemia with Improved Swarm Optimization of Deep Features.

White Blood Cell (WBC) Leukaemia is caused by excessive production of leukocytes in the bone marrow, and image-based detection of malignant WBCs is im...

Detecting total hip replacement prosthesis design on plain radiographs using deep convolutional neural network.

Identifying the design of a failed implant is a key step in the preoperative planning of revision total joint arthroplasty. Manual identification of t...

Soft coagulation in robot-assisted partial nephrectomy without renorrhaphy: Comparison with standard suture.

Comparison Studies of "Ultrathin Parenchyma" Resection and Sharp Dissection in Robotic Partial Nephrectomy for Renal Tumors.

The aim of this study was to introduce the "ultrathin parenchyma" resection in a robot-assisted partial nephrectomy (RAPN) via the retroperitoneal ap...

Continuous Pain Assessment Using Ensemble Feature Selection from Wearable Sensor Data.

Sickle cell disease (SCD) is a red blood cell disorder complicated by lifelong issues with pain. Management of SCD related pain is particularly challe...