Interest of Chest CT to Assess the Prognosis of SARS-CoV-2 Pneumonia: An In-Hospital-Based Experience in Sub-Saharan Africa by Serge Emmanuel Obe -A- Ndzem Holenn, Tacite Kpanya Mazoba, Désiré Yaya Mukanga, Tyna Bongosepe Zokere, Djo Lungela, Jean-Robert Makulo, Steve Ahuka, Angèle Tanzia Mbongo, Antoine Aundu Molua

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Deep Learning-Based Postural Asymmetry Detection Through Pressure Mat by Iker Azurmendi, Manuel Gonzalez, Gustavo García, Ekaitz Zulueta, Elena Martín

“…In this paper we will discuss the application of deep learning algorithms in the analysis of pressure data for the detection of postural asymmetries in 139 patients aged 3 to 20 years. …”
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Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation. by Soraya Khanmohmmadi, Toktam Khatibi, Golnaz Tajeddin, Elham Akhondzadeh, Amir Shojaee

“…Although convolutional neural networks (CNNs) are commonly used for detecting these conditions, their performance is inadequate when applied to our heterogeneous and limited-scale EEG data. …”
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Tourism product consumers clustering for developing the tailored marketing mix by Nataliya Chukhray, Kateryna Yarmola, Andrii Chukhrai

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Lightweight Brain Tumor Segmentation Through Wavelet-Guided Iterative Axial Factorization Attention by Yueyang Zhong, Shuyi Wang, Yuqing Miao, Tao Zhang, Haoliang Li

“…Background/Objectives: The accurate and efficient segmentation of brain tumors from 3D MRI data remains a significant challenge in medical imaging. …”
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A novel deep learning approach for predicting stone-free rates post-ESWL on uncontrasted CT by Ozgur Efiloglu, Muhammed Yildirim, Kadir Yildirim, Harun Bingol, Mustafa Kaan Akalin, Meftun Culpan, Bilal Alatas, Asif Yildirim

“…In conclusion, we analyzed the effect of ESWL treatment using different artificial intelligence methods and found that the prediction accuracy was 94% on average. Results were obtained from seven different convolutional neural networks (CNNs) and two textural-based models in the study. …”
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Deep Learning Evaluation of Glaucoma Detection Using Fundus Photographs in Highly Myopic Populations by Yen-Ying Chiang, Ching-Long Chen, Yi-Hao Chen

“…We used two classification models with the convolutional block attention module (CBAM), an attention mechanism module that enhances the performance of convolutional neural networks (CNNs), to investigate glaucoma cases. The learning data of this experiment were evaluated through fivefold cross-validation. …”
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Comprehensive Stress-Based De Novo Transcriptome Assembly and Annotation of Guar (Cyamopsis tetragonoloba (L.) Taub.): An Important Industrial and Forage Crop by Fahad Al-Qurainy, Aref Alshameri, Abdel-Rhman Gaafar, Salim Khan, Mohammad Nadeem, Abdulhafed Abdullah Alameri, Mohamed Tarroum, Muhammad Ashraf

“…Taub.) has the ability to endure heat, drought, and mild salinity. A complete image on its genic architecture will promote our understanding about gene expression networks and different tolerance mechanisms at the molecular level. …”
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Using artificial intelligence methods for shear travel time prediction: A case study of Facha member, Sirte basin, Libya by Bahia Ben Ghawar, Moncef Zairi, Samir Bouaziz

“…Based on principle component analysis, two wireline data sets were chosen to build intelligent models for prediction of shear travel time. …”
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Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

“…In the current BCI research context, apart from predicting extremity movements, recent BCI studies have been interested in accurately predicting finger movements of the same hand using different pattern recognition methods over EEG data collected based on motor imagery (MI), through which a mental image of the desired action is generated when a person ideally simulates or imagines carrying out a certain motor task. …”
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