ArticleDiagnostics (Basel, Switzerland)2021
DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 citations in OpenAlex.
- Artificial intelligence for the diagnosis of retinopathy of prematurity: A systematic review of current algorithms.Eye (London, England) · 2023Pooled it
- Review
- Enhancing deep learning telemedicine for retinopathy of prematurity: current evidence and opportunities for improvement.Eye (London, England) · 2026Article
- Deep learning algorithms for timely diagnosis of retinopathy of prematurity requiring treatment.Eye (London, England) · 2026Article
- Harnessing infrared thermography and multi-convolutional neural networks for early breast cancer detection.Scientific reports · 2025Article
- FARFUM-RoP, A dataset for computer-aided detection of Retinopathy of Prematurity.Scientific data · 2024Article
- Skin cancer classification leveraging multi-directional compact convolutional neural network ensembles and gabor wavelets.Scientific reports · 2024Article
- ADHD-AID: Aiding Tool for Detecting Children's Attention Deficit Hyperactivity Disorder via EEG-Based Multi-Resolution Analysis and Feature Selection.Biomimetics (Basel, Switzerland) · 2024Article
- Automatic zoning for retinopathy of prematurity with a key area location system.Biomedical optics express · 2024Article
- A Straightforward Bifurcation Pattern-Based Fundus Image Registration Method.Sensors (Basel, Switzerland) · 2023Article
- RiPa-Net: Recognition of Rice Paddy Diseases with Duo-Layers of CNNs Fostered by Feature Transformation and Selection.Biomimetics (Basel, Switzerland) · 2023Article
- Enhancement of Diabetic Retinopathy Prognostication Using Deep Learning, CLAHE, and ESRGAN.Diagnostics (Basel, Switzerland) · 2023Article
- RADIC:A tool for diagnosing COVID-19 from chest CT and X-ray scans using deep learning and quad-radiomics.Chemometrics and intelligent laboratory systems : an international journal sponsored by the Chemometrics Society · 2023Article
- GabROP: Gabor Wavelets-Based CAD for Retinopathy of Prematurity Diagnosis via Convolutional Neural Networks.Diagnostics (Basel, Switzerland) · 2023Article
- Latest Trends in Retinopathy of Prematurity: Research on Risk Factors, Diagnostic Methods and Therapies.International journal of general medicine · 2023Review
- Research progress in artificial intelligence assisted diabetic retinopathy diagnosis.International journal of ophthalmology · 2023Article
- A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.Sensors (Basel, Switzerland) · 2022Article
- A Framework for Lung and Colon Cancer Diagnosis via Lightweight Deep Learning Models and Transformation Methods.Diagnostics (Basel, Switzerland) · 2022Article
- A wavelet-based deep learning pipeline for efficient COVID-19 diagnosis via CT slices.Applied soft computing · 2022Article
- Trends in Neonatal Ophthalmic Screening Methods.Diagnostics (Basel, Switzerland) · 2022Review
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Retinopathy of Prematurity (ROP) affects preterm neonates and could cause blindness. Deep Learning (DL) can assist ophthalmologists in the diagnosis of ROP. This paper proposes an automated and reliable diagnostic tool based on DL techniques called DIAROP to support the ophthalmologic diagnosis of ROP. It extracts significant features by first obtaining spatial features from the four Convolution Neural Networks (CNNs) DL techniques using transfer learning and then applying Fast Walsh Hadamard Transform (FWHT) to integrate these features. Moreover, DIAROP explores the best-integrated features extracted from the CNNs that influence its diagnostic capability. The results of DIAROP indicate that DIAROP achieved an accuracy of 93.2% and an area under receiving operating characteristic curve (AUC) of 0.98. Furthermore, DIAROP performance is compared with recent ROP diagnostic tools. Its promising performance shows that DIAROP may assist the ophthalmologic diagnosis of ROP.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.