Article

Morphology-based classification of sickle cell disease and β-thalassemia using a low-cost automated microscope and machine learning

2024-09-23

Abstract excerpt

Sickle cell disease (SCD) and β-thalassemia are the most common monogenic diseases, disproportionately affecting low- and middle-income countries, where low-cost and accurate diagnostic tools are needed to reduce the global disease burden. Although the sickling test is commonly used to screen for the sickle mutation, it cannot distinguish between the asymptomatic sickle cell trait (SCT) and SCD, or identify β-thal...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: dfa5873e-d235-5367-9a02-80aee3bd28ea
DOI: 10.1101/2024.09.21.24314128

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Morphology-based classification of sickle cell disease and β-thalassemia using a low-cost automated microscope and machine learningDOI 10.1101/2024.09.21.24314128Read

Decoupling Detection and Classification to Improve Morphological Phenotype Analysis of Sickle Red Blood Cells in Full-Scope MicroscopySemantic proximity Read

Octopi 2.0: Open and Scalable Microscopy Platform for AI-powered Diagnostic ApplicationsSemantic proximity Read

Differential sensitivity to hypoxia enables shape‐based classification of sickle cell disease and trait blood samples at point of careSemantic proximity Read

A Dual-Modal Machine Learning Framework Integrating Red Blood Indices and Smartphone-Captured Microscopic Images for β-Thalassemia ScreeningSemantic proximity Read

Label-Free Optical Marker for Red-Blood-Cell Phenotyping of Inherited Anemias.Semantic proximity Read

Computing Sickle Erythrocyte Health Index Based on Quantitative Phase Imaging and Machine LearningSemantic proximity Read

Integrating deep learning with microfluidics for biophysical classification of sickle red blood cellsSemantic proximity Read

An algorithm to detect overlapping red blood cells for sickle cell disease diagnosisSemantic proximity Read

Machine learning-based approaches for identifying human blood cells harboring CRISPR-mediated fetal chromatin domain ablations.Semantic proximity Read

Deep Optical Blood Analysis: COVID-19 Detection as a Case Study in Next Generation Blood ScreeningSemantic proximity Read

A New Method for Screening Thalassemia Patients Using Mid Infrared SpectroscopySemantic proximity Read

A Precision Screening Framework for Thalassemia in a High-Mobility Population: Integrating 3D Phenotypic Mapping and Genotype-Specific ThresholdsSemantic proximity Read