Using CNN with Bayesian optimization to identify cerebral micro-bleeds
Sign Up to like & getrecommendations! Published in 2020 at "Machine Vision and Applications"
DOI: 10.1007/s00138-020-01087-0
Abstract: This article studies the problem of detecting cerebral micro-bleeds (CMBs) using a convolutional neural network (CNN). Cerebral micro-bleeds (CMBs) are increasingly recognized neuroimaging findings, occurring with cerebrovascular diseases, dementia, and normal aging. Naturally enough, it… read more here.
Keywords: cerebral micro; micro bleeds; using cnn; bayesian optimization ... See more keywords
A deep learning framework using CNN and stacked Bi-GRU for COVID-19 predictions in India
Sign Up to like & getrecommendations! Published in 2021 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-021-01988-1
Abstract: The novel coronavirus infection (COVID-19) first appeared in Wuhan, China, in December 2019. COVID-19 declared as a global pandemic by the WHO was the most rapidly spreading disease all across the world. India, the second… read more here.
Keywords: cnn stacked; framework; using cnn; deep learning ... See more keywords
Spectrum Sensing in Cognitive Radio Using CNN-RNN and Transfer Learning
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DOI: 10.1109/access.2022.3216877
Abstract: Cognitive radio has been proposed to improve spectrum utilization in wireless communication. Spectrum sensing is an essential component of cognitive radio. The traditional methods of spectrum sensing are based on feature extraction of a received… read more here.
Keywords: spectrum sensing; transfer learning; spectrum; cognitive radio ... See more keywords
Predicting MicroRNA Sequence Using CNN and LSTM Stacked in Seq2Seq Architecture
Sign Up to like & getrecommendations! Published in 2020 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2019.2936186
Abstract: CNN and LSTM have proven their ability in feature extraction and natural language processing, respectively. So, we tried to use their ability to process the language of RNAs, i.e., predicting sequence of microRNAs using the… read more here.
Keywords: mml; math; sequence; using cnn ... See more keywords
Automated detection of coronary artery disease comparing arterial fat accumulation using CNN
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Electronic Imaging"
DOI: 10.1117/1.jei.31.5.051405
Abstract: Abstract. Congenital heart failure (CHF) due to congestion in the blood is a serious cardiac problem correlated with crippling symptoms and leading to a rising death rate, monumental health care spending, and reduced quality of… read more here.
Keywords: fat accumulation; disease; automated detection; heart ... See more keywords
Peripapillary atrophy classification using CNN deep learning for glaucoma screening
Sign Up to like & getrecommendations! Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0275446
Abstract: Glaucoma is the second leading cause of blindness worldwide, and peripapillary atrophy (PPA) is a morphological symptom associated with it. Therefore, it is necessary to clinically detect PPA for glaucoma diagnosis. This study was aimed… read more here.
Keywords: glaucoma; classification; cnn deep; deep learning ... See more keywords
Expert System for Mandibular Condyle Detection and Osteoarthritis Classification in Panoramic Imaging Using R-CNN and CNN
Sign Up to like & getrecommendations! Published in 2020 at "Applied Sciences"
DOI: 10.3390/app10217464
Abstract: Temporomandibular joint osteoarthritis (TMJ OA) is a degenerative condition of the TMJ led by a pathological tissue response of the joint under mechanical loading. It is characterized by the progressive destruction of the internal surfaces… read more here.
Keywords: osteoarthritis; using cnn; condyle detection; panoramic imaging ... See more keywords