Article

Generalizable deep neural networks for image quality classification of cervical images

2024-01-18

Abstract excerpt

<title>Abstract</title> <p>Successful translation of artificial intelligence (AI) models into clinical practice, across clinical domains, is frequently hindered by the lack of image quality control. Diagnostic models are often trained on images with no denotation of image quality in the training data; this, in turn, can lead to misclassifications by these models when implemented in the clinical setting. In the ca...

Topics

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

Identifiers and source

Literature Corpus work: 8edea0e4-04a2-5a3f-8c69-87263b0d3a5e
DOI: 10.21203/rs.3.rs-3845696/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Generalizable deep neural networks for image quality classification of cervical imagesDOI 10.21203/rs.3.rs-3845696/v1Read

Assessing generalizability of an AI-based visual test for cervical cancer screeningSemantic proximity Read

Multi-Modal Deep Learning Architecture for Improved Colposcopy Image ClassificationSemantic proximity Read

Multi-Modal Deep Learning Architecture for Improved Colposcopy Image ClassificationSemantic proximity Read

Robust Whole Slide Image Analysis for Cervical Cancer Screening Using Deep LearningSemantic proximity Read

Detection and Classification of Cervical Cancer Using Optimized Deep Learning ApproachSemantic proximity Read

Internal Validation of Automated Visual Evaluation (AVE) on Smartphone Images for Cervical Cancer Screening in a Prospective Study in ZambiaSemantic proximity Read

Synthesis of diagnostic quality cancer pathology imagesSemantic proximity Read

Enhancing Histological Cancer Cell Detection: Integrating XAI with Deep Learning for Improved Accuracy, Interpretability, and Clinical TrustSemantic proximity Read

CINNAMON-GUI: Revolutionizing Pap Smear Analysis with CNN-Based Digital Pathology Image ClassificationSemantic proximity Read

A Unified Vision Transformer and Convolutional Neural Network Framework for Multi-Domain Cancer ClassificationSemantic proximity Read

Cross-country generalizability of foundation models for cervical cancer screenings on H&E whole slide imagesSemantic proximity Read

Explainable Two-Phase Transfer Learning for Accurate Multi-Class Cervical Cell Classification from Optical Microscopy ImagesSemantic proximity Read