Review of Different Types of Neural Network Architectures by T. L. Makosso, A. Almaktoof, K. Abo-Al-Ez

“…Which leads to intelligent computational systems such as artificial neural networks. It is developed so that artificial neurons combined together would behave like a human brain. …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

“…This study compares the effectiveness of a Decision Tree Classifier and an Artificial Neural Network (ANN) in predicting Diabetes Mellitus. …”
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Harvesting Solar Energy: Prediction of Daily Global Horizontal Irradiance Using Artificial Neural Networks and Assessment of Electrical Energy of Photovoltaic at North Eastern Ethi... by Tegenu A. Woldegiyorgis, Abera D. Assamnew, Gezahegn A. Desalegn, Sentayehu Y. Mossie

“…Thus, the objectives of this article were: (i) assessing daily global horizontal irradiance using network types‐activation functions of artificial neural network (ANN); and (ii) evaluating the daily energy delivered to and available on photovoltaic (PV) cells of GaAs at Kemissie, Woldiya, and Hayk, in the northeastern part of Ethiopia. …”
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Computer graphics processing technology based on GIS model and its application by Quanpeng Ji

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AI post-intervention operational and functional outcomes prediction in ischemic stroke patients using MRIs by Emily Wittrup, John Reavey-Cantwell, Aditya S. Pandey, Dennis J. Rivet II, Kayvan Najarian

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Net2Brain: a toolbox to compare artificial vision models with human brain responses by Domenic Bersch, Domenic Bersch, Martina G. Vilas, Martina G. Vilas, Sari Saba-Sadiya, Timothy Schaumlöffel, Timothy Schaumlöffel, Kshitij Dwivedi, Christina Sartzetaki, Radoslaw M. Cichy, Radoslaw M. Cichy, Radoslaw M. Cichy, Gemma Roig, Gemma Roig

“…In cognitive neuroscience, the integration of deep neural networks (DNNs) with traditional neuroscientific analyses has significantly advanced our understanding of both biological neural processes and the functioning of DNNs. …”
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PHILOSOPHICAL AND ANTHROPOLOGICAL IMPORTANCE OF DEVELOPMENT OF ARTIFICIALLY CREATED INTELLIGENT SYSTEMS by Yu. D. Gensitskiy

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Analyzing analytical and software methods for deep foundation analysis and presenting a new solution for determining pile capacity using the PDA test by Ahmad Honarjoo, Vahed Ghiasi

“…In this system, the pile capacity for a chosen number of piles was finally determined by successfully combining a number of neural networks. The suggested system extends earlier neural networks for a comparable function and uses a self-organizing neural network for a set of data in training, testing, and valid datasets. …”
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Integrating weighted gene co-expression network analysis and machine learning to elucidate neural characteristics in a mouse model of depression by Jinli Gao, Qinglang Wang, Jie Liu, Siqian Zheng, Jiahong Liu, Zhiyong Gao, Cheng Zhu

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Elements of artificial intelligence in a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction of ischemic or... by O. A. Osipova, A. V. Kontsevaya, V. V. Demko, E. V. Gosteva, A. A. Komisov, А. A. Kuzub, A. V. Serdyukova, A. S. Brizhaneva, R. N. Shepel, O. M. Drapkina

“…The result of this function is a parameter vector: AL, TNF-α, MMP-9, SI and quality of life (QOL). …”
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A hierarchical reinforcement learning approach for energy‐aware service function chain dynamic deployment in IoT by Shuyi Wang, Haotong Cao, Longxiang Yang

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Artificial Neural Network and response surface methodology modeling-based optimization approach for the ultrasonication-assisted extraction of phenolics from mustard (BARI Sharisa-... by Md. Waziur Rahman Chy, Tanvir Ahmed, Robin Sarkar, Md. Zohurul Islam, Md. Rahmatuzzaman Rana

“…Response Surface Methodology (RSM) and an Artificial Neural Network (ANN) multilayer perceptron model were employed to improve reliability, with hyperparameter tuning focused on the number of neurons and activation functions to prevent overfitting. …”
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An Innovative Artificial Intelligence Classification Model for Non-Ischemic Cardiomyopathy Utilizing Cardiac Biomechanics Derived from Magnetic Resonance Imaging by Liqiang Fu, Peifang Zhang, Liuquan Cheng, Peng Zhi, Jiayu Xu, Xiaolei Liu, Yang Zhang, Ziwen Xu, Kunlun He

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Bio-realistic and versatile artificial dendrites made of anti-ambipolar transistors by Yifei Yang, Mingkun Xu, Tianhang Zhang, Chenfei Miao, Juan Lyu, Jing Pei, Peng Li, Guoqi Li, Si Wu, Huanglong Li

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THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY – A REVIEW OF THE BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES by Mariana Yordanova

“…Deep learning, especially deep convolutional neural networks (CNNs), has become a prominent approach, mimicking brain functions to process images through multiple layers. …”
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Detection of structural-functional coupling abnormalities using multimodal brain networks in Alzheimer’s disease: A comparison of three computational models by Yinping Lu, Luyao Wang, Toshiya Murai, Jinglong Wu, Dong Liang, Zhilin Zhang

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Ethical Aspects of the Influence of Neural Networks on the Lives of Students in the Context of a Sociological Approach (using the Example of Students of the IT Department of ETU) by A. S. Kurapova, S. V. Kurapov, A. D. Derzhavina, N. V. Shatilo

“…The article is devoted to the analysis of the development and implementation of artificial intelligence systems, in particular neural networks, in the life of students. …”
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Optimization of the Inorganic Salts in Coenzyme Q₁₀ Fermentation Medium of <i>Rhodobacter sphaeroides</i> Based on Uniform Design and Artificial Neural Network and Genet... by Yi Zheng, Yujun Xiao, Shuling Tang, Junpeng Li, Yingzi Wu, Yong Zhou

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AIpollen: An Analytic Website for Pollen Identification Through Convolutional Neural Networks by Xingchen Yu, Jiawen Zhao, Zhenxiu Xu, Junrong Wei, Qi Wang, Feng Shen, Xiaozeng Yang, Zhonglong Guo

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Deep Neural Networks for Accurate Depth Estimation with Latent Space Features by Siddiqui Muhammad Yasir, Hyunsik Ahn

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