ArticleIT professional2021
Real-Time Diagnosis System of COVID-19 Using X-Ray Images and Deep Learning.
Article in IT professional, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Meta-learning for real-world class incremental learning: a transformer-based approach.Scientific reports · 2024Article
- Computer-aided analysis of radiological images for cancer diagnosis: performance analysis on benchmark datasets, challenges, and directions.EJNMMI reports · 2024Review
- Efficient lung cancer detection using computational intelligence and ensemble learning.PloS one · 2024Article
- Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review.Sensors (Basel, Switzerland) · 2022Review
- A Comprehensive Review of Machine Learning Used to Combat COVID-19.Diagnostics (Basel, Switzerland) · 2022Review
- Microscopic segmentation and classification of COVID-19 infection with ensemble convolutional neural network.Microscopy research and technique · 2022Article
- An intelligence design for detection and classification of COVID19 using fusion of classical and convolutional neural network and improved microscopic features selection approach.Microscopy research and technique · 2021Article
- Machine learning techniques to detect and forecast the daily total COVID-19 infected and deaths cases under different lockdown types.Microscopy research and technique · 2021Article
- Viral reverse engineering using Artificial Intelligence and big data COVID-19 infection with Long Short-term Memory (LSTM).Environmental technology & innovation · 2021Article
- COVID-19 Diagnosis Using Capsule Network and FuzzyBioMed research international · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The novel coronavirus named COVID-19 has quickly spread among humans worldwide, and the situation remains hazardous to the health system. The existence of this virus in the human body is identified through sputum or blood samples. Furthermore, computed tomography (CT) or X-ray has become a significant tool for quick diagnoses. Thus, it is essential to develop an online and real-time computer-aided diagnosis (CAD) approach to support physicians and avoid further spreading of the disease. In this research, a convolutional neural network (CNN) -based Residual neural network (ResNet50) has been employed to detect COVID-19 through chest X-ray images and achieved 98% accuracy. The proposed CAD system will receive the X-ray images from the remote hospitals/healthcare centers and perform diagnostic processes. Furthermore, the proposed CAD system uses advanced load balancer and resilience features to achieve fault tolerance with zero delays and perceives more infected cases during this pandemic.
Identifiers
What OpenQuestion holds
Registered trials
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.