AI Medical Compendium Journal:
International journal of laboratory hematology

Showing 1 to 10 of 22 articles

An Efficient Acute Lymphoblastic Leukemia Screen Framework Based on Multi-Modal Deep Neural Network.

International journal of laboratory hematology
BACKGROUND: Acute lymphoblastic leukemia (ALL) is a leading cause of death among pediatric malignancies. Early diagnosis of ALL is crucial for minimizing misdiagnosis, improving survival rates, and ensuring the implementation of precise treatment pla...

Deep Learning-Based Blood Abnormalities Detection as a Tool for VEXAS Syndrome Screening.

International journal of laboratory hematology
INTRODUCTION: VEXAS is a syndrome described in 2020, caused by mutations of the UBA1 gene, and displaying a large pleomorphic array of clinical and hematological features. Nevertheless, these criteria lack significance to discriminate VEXAS from othe...

Establishing reflex test rules for platelet fluorescent counting method using machine learning models on Sysmex XN-series hematology analyzer.

International journal of laboratory hematology
INTRODUCTION: The platelet fluorescent counting (PLT-F) method is utilized as a reflex test method following the initial test of the platelet impedance counting (PLT-I) method in clinical practice on the Sysmex XN-series automated hematology analyzer...

Evaluation of artificial intelligence-assisted morphological analysis for platelet count estimation.

International journal of laboratory hematology
INTRODUCTION: This study aims to assess the performance of the platelet count estimation using artificial intelligence technology on the MC-80 digital morphology analyzer.

Construction of the prediction model for multiple myeloma based on machine learning.

International journal of laboratory hematology
INTRODUCTION: The global burden of multiple myeloma (MM) is increasing every year. Here, we have developed machine learning models to provide a reference for the early detection of MM.

Automatic classification and segmentation of blast cells using deep transfer learning and active contours.

International journal of laboratory hematology
INTRODUCTION: Acute lymphoblastic leukemia (ALL) presents a formidable challenge in hematological malignancies, necessitating swift and precise diagnostic techniques for effective intervention. The conventional manual microscopy of blood smears, alth...

Schistocyte detection in artificial intelligence age.

International journal of laboratory hematology
Schistocytes are fragmented red blood cells produced as a result of mechanical damage to erythrocytes, usually due to microangiopathic thrombotic diseases or mechanical factors. The early laboratory detection of schistocytes has a critical impact on ...

A comparative evaluation of three consecutive artificial intelligence algorithms released by Techcyte for identification of blasts and white blood cells in abnormal peripheral blood films.

International journal of laboratory hematology
INTRODUCTION: Digital pathology artificial intelligence (AI) platforms have the capacity to improve over time through "deep machine learning." We have previously reported on the accuracy of peripheral white blood cell (WBC) differential and blast ide...

Artificial intelligence and the blood film: Performance of the MC-80 digital morphology analyzer in samples with neoplastic and reactive cell types.

International journal of laboratory hematology
INTRODUCTION: Implementing artificial intelligence-based instruments in hematology laboratories requires evidence of efficiency in classifying pathological cells. In two-Universities, we assessed the performance of the Mindray® MC-80 for hematology p...

Applied machine learning in hematopathology.

International journal of laboratory hematology
An increasing number of machine learning applications are being developed and applied to digital pathology, including hematopathology. The goal of these modern computerized tools is often to support diagnostic workflows by extracting and summarizing ...