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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 ...
MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
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Springer Science and Business Media Deutschland GmbH
, 2022 , Article)
Electroencephalogram (EEG) signals suffer substantially from motion artifacts when recorded in ambulatory settings utilizing wearable sensors. Because the diagnosis of many neurological diseases is heavily reliant on clean ...
An optimized algorithm for optimal power flow based on deep learning
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Elsevier
, 2021 , Article)
With the increasing requirements for power system transient stability assessment, the research on power system transient stability assessment theory and methods requires not only qualitative conclusions about system transient ...
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. ...
Employing machine learning techniques in monitoring autocorrelated profiles
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Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
In profile monitoring, it is usually assumed that the observations between or within each profile are independent of each other. However, this assumption is often violated in manufacturing practice, and it is of utmost ...
Using artificial intelligence to improve body iron quantification: A scoping review
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Elsevier
, 2023 , Article Review)
This scoping review explores the potential of artificial intelligence (AI) in enhancing the screening, diagnosis, and monitoring of disorders related to body iron levels. A systematic search was performed to identify studies ...
Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks
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MDPI
, 2021 , Article)
Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming ...
PredictPTB: an interpretable preterm birth prediction model using attention-based recurrent neural networks
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BioMed Central Ltd
, 2022 , Article)
Background: Early identification of pregnant women at risk for preterm birth (PTB), a major cause of infant mortality and morbidity, has a significant potential to improve prenatal care. However, we lack effective predictive ...
BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data
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Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge ...
An active learning method for diabetic retinopathy classification with uncertainty quantification
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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 ...