44   Artículos

 
en línea
Hassen Louati, Ali Louati, Rahma Lahyani, Elham Kariri and Abdullah Albanyan    
Responding to the critical health crisis triggered by respiratory illnesses, notably COVID-19, this study introduces an innovative and resource-conscious methodology for analyzing chest X-ray images. We unveil a cutting-edge technique that marries neural... ver más
Revista: Information    Formato: Electrónico

 
en línea
Shoffan Saifullah and Rafal Drezewski    
Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study of the efficacy of particle swarm optimization (PSO) combined with histogram equalization (HE) preproc... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Ku Muhammad Naim Ku Khalif, Woo Chaw Seng, Alexander Gegov, Ahmad Syafadhli Abu Bakar and Nur Adibah Shahrul    
Convolutional Neural Networks (CNNs) have garnered significant utilisation within automated image classification systems. CNNs possess the ability to leverage the spatial and temporal correlations inherent in a dataset. This study delves into the use of ... ver más
Revista: Information    Formato: Electrónico

 
en línea
Qingji Guan, Qinrun Chen and Yaping Huang    
Chest X-ray image classification suffers from the high inter-similarity in appearance that is vulnerable to noisy labels. The data-dependent and heteroscedastic characteristic label noise make chest X-ray image classification more challenging. To address... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Shubham Mathesul, Debabrata Swain, Santosh Kumar Satapathy, Ayush Rambhad, Biswaranjan Acharya, Vassilis C. Gerogiannis and Andreas Kanavos    
The COVID-19 pandemic has posed significant challenges in accurately diagnosing the disease, as severe cases may present symptoms similar to pneumonia. Real-Time Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) is the conventional diagnostic tech... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Domantas Kuzinkovas and Sandhya Clement    
Advances in the field of image classification using convolutional neural networks (CNNs) have greatly improved the accuracy of medical image diagnosis by radiologists. Numerous research groups have applied CNN methods to diagnose respiratory illnesses fr... ver más
Revista: Information    Formato: Electrónico

 
en línea
Tarik El Lel, Mominul Ahsan and Julfikar Haider    
Starting in late 2019, the coronavirus SARS-CoV-2 began spreading around the world and causing disruption in both daily life and healthcare systems. The disease is estimated to have caused more than 6 million deaths worldwide [WHO]. The pandemic and the ... ver más
Revista: Computers    Formato: Electrónico

 
en línea
Prajoy Podder, Fatema Binte Alam, M. Rubaiyat Hossain Mondal, Md Junayed Hasan, Ali Rohan and Subrato Bharati    
Due to its high transmissibility, the COVID-19 pandemic has placed an unprecedented burden on healthcare systems worldwide. X-ray imaging of the chest has emerged as a valuable and cost-effective tool for detecting and diagnosing COVID-19 patients. In th... ver más
Revista: Computers    Formato: Electrónico

 
en línea
Naeem Ullah, Javed Ali Khan, Sultan Almakdi, Mohammad Sohail Khan, Mohammed Alshehri, Dabiah Alboaneen and Asaf Raza    
The suspected cases of COVID-19 must be detected quickly and accurately to avoid the transmission of COVID-19 on a large scale. Existing COVID-19 diagnostic tests are slow and take several hours to generate the required results. However, on the other han... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Sanjeevkumar Hatture,Madhu Koravanavar,Rashmi Saini     Pág. 94 - 100
In recent years there is heavy demand in healthcare systems due to COVID-19 pandemic. The COVID-19 will mainly cause the Lung infections, which affected the whole world very badly during last two years and still continues to affecting the world, this cau... ver más
Revista: International Journal of Open Information Technologies    Formato: Electrónico

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