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Reliable tuberculosis detection using chest X-ray with deep learning, segmentation and visualization
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial infection and is one of the top 10 leading causes of death. Accurate and early detection of TB is very important, otherwise, it could be life-threatening. ...
Transfer learning with deep Convolutional Neural Network (CNN) for pneumonia detection using chest X-ray
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MDPI AG
, 2020 , Article)
Pneumonia is a life-threatening disease, which occurs in the lungs caused by either bacterial or viral infection. It can be life-endangering if not acted upon at the right time and thus the early diagnosis of pneumonia is ...
COVID-19 infection map generation and detection from chest X-ray images
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Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
Computer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment and prevent the spread of the virus. Numerous studies have proposed to use Deep ...
DL-CRC: Deep learning-based chest radiograph classification for covid-19 detection: A novel approach
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
With the exponentially growing COVID-19 (coronavirus disease 2019) pandemic, clinicians continue to seek accurate and rapid diagnosis methods in addition to virus and antibody testing modalities. Because radiographs such ...
Disaster related social media content processing for sustainable cities
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Elsevier
, 2021 , Article)
The current study offers a hybrid convolutional neural networks (CNN) model that filters relevant posts and categorises them into several humanitarian classifications using both character and word embedding of textual ...
An active learning method for diabetic retinopathy classification with uncertainty quantification
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Article)
In recent years, deep learning (DL) techniques have provided state-of-the-art performance in medical imaging. However, good quality (annotated) medical data is in general hard to find due to the usually high cost of medical ...
AI-enabled remote monitoring of vital signs for COVID-19: methods, prospects and challenges
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Springer
, 2021 , Article)
The COVID-19 pandemic has overwhelmed the existing healthcare infrastructure in many parts of the world. Healthcare professionals are not only over-burdened but also at a high risk of nosocomial transmission from COVID-19 ...
Advance Warning Methodologies for COVID-19 Using Chest X-Ray Images
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Coronavirus disease 2019 (COVID-19) has rapidly become a global health concern after its first known detection in December 2019. As a result, accurate and reliable advance warning system for the early diagnosis of COVID-19 ...
Security concerns on machine learning solutions for 6G networks in mmWave beam prediction
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Elsevier B.V.
, 2022 , Article)
6G – sixth generation – is the latest cellular technology currently under development for wireless communication systems. In recent years, machine learning (ML) algorithms have been applied widely in various fields, such ...
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ...