Presentation of a Novel Method for Prediction of Traffic with Climate Condition Based on Ensemble Learning of Neural Architecture Search (NAS) and Linear Regression

Artin, Javad; Valizadeh, Amin; Ahmadi, Mohsen; Kumar, Sathish; Sharifi, Abbas

doi:10.1155/2021/8500572

Cited by 28 publications

(22 citation statements)

References 63 publications

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“…Machine learning is also widely used in biological applications, such as optimization [ 63 , 64 ], feature extraction [ 65 , 66 ], and diagnosis of tumors [ 67 ]. The applications of deep learning method are infection disease detection [ 68 ], economical application [ 69 ], cancer research [ 70 ], brain tumor detection [ 71 , 72 ], fatigue detection [ 73 ], environmental science [ 74 ], federated learning [ 75 ], facial expression detection [ 76 ], and healthcare analysis [ 77 ]. Moreover, some metaheuristic methods are aquila optimization [ 78 ], reptile search method [ 79 ], genetic algorithm [ 74 ], and so on [ 80 ].…”

Section: Literature Reviewmentioning

confidence: 99%

GC-CNNnet: Diagnosis of Alzheimer’s Disease with PET Images Using Genetic and Convolutional Neural Network

Amini

Pedram

Moradi

et al. 2022

Computational Intelligence and Neuroscience

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There is a wide variety of effects of Alzheimer’s disease (AD), a neurodegenerative disease that can lead to cognitive decline, deterioration of daily life, and behavioral and psychological changes. A polymorphism of the ApoE gene ε 4 is considered a genetic risk factor for Alzheimer’s disease. The purpose of this paper is to demonstrate that single-nucleotide polymorphic markers (SNPs) have a causal relationship with quantitative PET imaging traits. Additionally, the classification of AD is based on the frequency of brain tissue variations in PET images using a combination of k-nearest-neighbor (KNN), support vector machine (SVM), linear discrimination analysis (LDA), and convolutional neural network (CNN) techniques. According to the results, the suggested SNPs appear to be associated with quantitative traits more strongly than the SNPs in the ApoE genes. Regarding the classification result, the highest accuracy is obtained by the CNN with 91.1%. These results indicate that the KNN and CNN methods are beneficial in diagnosing AD. Nevertheless, the LDA and SVM are demonstrated with a lower level of accuracy.

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Section: Literature Reviewmentioning

confidence: 99%

GC-CNNnet: Diagnosis of Alzheimer’s Disease with PET Images Using Genetic and Convolutional Neural Network

Amini

Pedram

Moradi

et al. 2022

Computational Intelligence and Neuroscience

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“…These aerosols are caused by coughing, sneezing, or talking and can stay in the air for hours [ 29 , 30 ]. Significantly pollute the air and environmental surfaces [ 31 ]. The half-life of the virus in aerosols is about one hour [ 32 ], which is twice the half-life of influenza viruses [ 33 , 34 ].…”

Section: Virus Transmission Waysmentioning

confidence: 99%

“…Of course, the persistence of the virus in aquatic and wastewater environments depends on other environmental factors such as temperature, sunlight, and organic compounds [ 107 ] (see Figure 9 ). According to the latest WHO report, the human coronavirus has not yet been transmitted through contaminated drinking water [ 31 , 108 ]. Coated viruses are generally more sensitive to oxidants and may be inactivated faster than nonpathogenic human intestinal viruses in contact with water oxidants [ 31 ].…”

Section: Climate Indicatorsmentioning

confidence: 99%

Human Responses in Public Health Emergencies for Infectious Disease Control: An Overview of Controlled Topologies for Biomedical Applications

Naseri

Aliashrafzadeh

Otadi

et al. 2022

Contrast Media & Molecular Imaging

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COVID-19 originated in Wuhan city of Hubei Province in China in December three years ago. Since then, it has spread to more than 210 countries and territories. This disease is caused by Severe Acute Respiratory Syndrome Coronavirus 2. The virus has a size of one to two nanometers and a single-stranded positive RNA. Droplets spread the virus from coughing and sneezing. This condition causes coughing, fever, acute respiratory problems, and even death. According to the WHO, the virus can survive outside the body for several hours. This research aimed to determine how environmental factors influenced the COVID-19 virus’s survival and behavior, as well as its transmission, in a complex environment. Based on the results, virus transmissions are influenced by various human and environmental factors such as population distribution, travel, social behavior, and climate change. Environmental factors have not been adequately examined concerning the transmission of this epidemic. Thus, it is necessary to examine various aspects of prevention and control of this disease, including its effects on climate and other environmental factors.

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“…Each layer has a different task assigned to it. Feature extractor layers are made up of convolutions and subsampling layers [57,58].…”

Section: Convolutional Neural Network (Cnn)mentioning

confidence: 99%

Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning

et al. 2021

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Breast cancer is one of the main causes of death among women worldwide. Early detection of this disease helps reduce the number of premature deaths. This research aims to design a method for identifying and diagnosing breast tumors based on ultrasound images. For this purpose, six techniques have been performed to detect and segment ultrasound images. Features of images are extracted using the fractal method. Moreover, k-nearest neighbor, support vector machine, decision tree, and Naïve Bayes classification techniques are used to classify images. Then, the convolutional neural network (CNN) architecture is designed to classify breast cancer based on ultrasound images directly. The presented model obtains the accuracy of the training set to 99.8%. Regarding the test results, this diagnosis validation is associated with 88.5% sensitivity. Based on the findings of this study, it can be concluded that the proposed high-potential CNN algorithm can be used to diagnose breast cancer from ultrasound images. The second presented CNN model can identify the original location of the tumor. The results show 92% of the images in the high-performance region with an AUC above 0.6. The proposed model can identify the tumor’s location and volume by morphological operations as a post-processing algorithm. These findings can also be used to monitor patients and prevent the growth of the infected area.

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Presentation of a Novel Method for Prediction of Traffic with Climate Condition Based on Ensemble Learning of Neural Architecture Search (NAS) and Linear Regression

Cited by 28 publications

References 63 publications

GC-CNNnet: Diagnosis of Alzheimer’s Disease with PET Images Using Genetic and Convolutional Neural Network

GC-CNNnet: Diagnosis of Alzheimer’s Disease with PET Images Using Genetic and Convolutional Neural Network

Human Responses in Public Health Emergencies for Infectious Disease Control: An Overview of Controlled Topologies for Biomedical Applications

Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning

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