Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network–Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey by Pichsinee Choomung, Yupeng He, Masaaki Matsunaga, Kenji Sakuma, Taro Kishi, Yuanying Li, Shinichi Tanihara, Nakao Iwata, Atsuhiko Ota

“…To address these issues, we previously developed an artificial neural network (ANN)–based schizophrenia classification model (SZ classifier) using data from a large-scale Japanese web-based survey to enhance the comprehensiveness of schizophrenia case identification in the general population. …”
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Framework for user behavioural biometric identification using a multimodal scheme with keystroke trajectory feature and recurrent neural network on a mobile platform by Ka‐Wing Tse, Kevin Hung

“…In the user identification phase, a multistream recurrent neural network (RNN) is adopted. The results reveal that the proposed trajectory model performs well, and the multimodal scheme using an RNN with a late fusion method provides accurate identification results. …”
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Comparative Forecasting of Some Key Economic Indicators Using Artificial Neural Networks and Ordinary Differential Equations: A Case Study of the Turkish Economy by Bahatdin Daşbaşı, Murat Taşyürek

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A novel graph neural network based approach for influenza-like illness nowcasting: exploring the interplay of temporal, geographical, and functional spatial features by Jiajia Luo, Xuan Wang, Xiaomao Fan, Yuxin He, Xiangjun Du, Yao-Qing Chen, Yang Zhao

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Towards combining self-organizing maps (SOM) and convolutional neural network (CNN) for improving model accuracy: Application to malaria vectors phenotypic resistance by Komi Mensah Agboka, Elfatih M. Abdel-Rahman, Daisy Salifu, Brian Kanji, Frank T. Ndjomatchoua, Ritter A.Y. Guimapi, Sunday Ekesi, Landmann Tobias

Subjects: “…Combining Self-Organizing Maps (SOM) and Convolutional Neural Network (CNN) for improving model accuracy…”
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(m1,m2)-pseudo almost periodic solutions of Clifford-valued high-order fuzzy cellular neural networks with time delays by Bing Li, Ting Chen, Yongkun Li

Subjects: “…Clifford-valued high-order fuzzy cellular neural networks…”
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Multivariable Diagnostic Prediction Model to Detect Hormone Secretion Profile From T2W MRI Radiomics with Artificial Neural Networks in Pituitary Adenomas by Begumhan BAYSAL, Mehmet Bilgin ESER, Mahmut Bilal DOGAN, Muhammet Arif KURSUN

“…Objective: This study aims to develop neural networks to detect hormone secretion profiles in the pituitary adenomas based on T2 weighted magnetic resonance imaging (MRI) radiomics. …”
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Comparison of the Applicability of Two Reanalysis Products in Estimating Tall Tower Wind Based on Multiple Linear Regression and Artificial Neural Network in South China by Xiangxiang Li, Xiaochen Qin, Jun Yang, Weiming Xu

“…For each TTO, linear and nonlinear downscaling techniques, namely, multiple linear regression (MLR) and an artificial neural network (ANN), respectively, were adopted for the downscaling of the scalar wind speed and the corresponding U/V components. …”
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Evaluating the Performance of Aluminum Oxide Nanoparticle-Modified Asphalt Binder and Modelling the Viscoelastic Properties by Using Artificial Neural Networks and Support Vector Machines by Mustafa Alas, Sani Isah Abba, Shaban Ismael Albrka Ali, Abdur Rahim, Nur Izzi Md. Yusoff

“…In addition, heuristic modelling techniques, artificial neural networks (ANN), and support vector machines (SVM) were employed to predict the performance characteristics of AC by using the mechanical testing conditions. …”
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LANDMARC indoor positioning algorithm based on density-based spatial clustering of applications with noise–genetic algorithm–radial basis function neural network by Jingqiu Ren, Ke Bao, Guanghua Zhang, Li Chu, Weidang Lu

“…The threshold and weight of radial basis function neural network were optimized by genetic algorithm. With less data information, the relationship between the value of label signal strength and position coordinate could be established to improve the positioning accuracy of LANDMARC positioning algorithm. …”
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Pre-trained convolutional neural network with transfer learning by artificial illustrated images classify power Doppler ultrasound images of rheumatoid arthritis joints by Jun Fukae, Yoshiharu Amasaki, Yuichiro Fujieda, Yuki Sone, Ken Katagishi, Tatsunori Horie, Tamotsu Kamishima, Tatsuya Atsumi

“…Objective To study the classification performance of a pre-trained convolutional neural network (CNN) with transfer learning by artificial joint ultrasonography images in rheumatoid arthritis (RA). …”
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Comparison between traditional models and artificial neural networks as estimators of the growth of the Tigris scraper Capoeta umbla (Teleostei: Cyprinidae) in the Munzur River, Turkey by Ebru Ifakat Ozcan, Osman Serdar

“…Therefore, artificial neural networks models are an effective tool to describe body weight and length in fish. …”
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A holistic physics-informed neural network solution for precise destruction of breast tumors using focused ultrasound on a realistic breast model by Salman Lari, Hossein Rajabzadeh, Mohammad Kohandel, Hyock Ju Kwon

Subjects: “…physics-informed neural network…”
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Mapping of Agate-like Soil Cover Structures Based on a Multitemporal Soil Line Using Neural Network Filtering of Remote Sensing Data by Dmitry I. Rukhovich, Polina V. Koroleva, Alexey D. Rukhovich, Mikhail A. Komissarov

“…ASCSs were identified over large areas and soil maps of ASCSs were constructed using multitemporal spectral characteristics of the BSS in the form of multitemporal soil line coefficients. Neural networks were used to identify BSS on big remote sensing data. …”
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A Feature-Extraction-Based Lightweight Convolutional and Recurrent Neural Networks Adaptive Computing Model for Container Terminal Liner Handling Volume Forecasting by Bin Li, Yuqing He

“…Subsequently, a feature-extraction-based lightweight convolutional and recurrent neural network adaptive computing model (FEB-LCR-ACM) is presented initially to predict the LHV by the fusion of multiple deep learning algorithms and mechanisms, especially for the specific feature extraction package of tsfresh. …”
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3MT Competition (EUSIPCO2024): A peek into the black box: Insights into the functionality of complex-valued neural networks for multichannel speech enhancement by Annika Briegleb

“…Artificial neural networks (ANNs) have become an important part of signal processing research. …”
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Artificial Neural Networks as a Tool for High-Accuracy Prediction of In-Cylinder Pressure and Equivalent Flame Radius in Hydrogen-Fueled Internal Combustion Engines by Federico Ricci, Massimiliano Avana, Francesco Mariani

“…Additionally, the neural network effectively estimates the equivalent flame radius, maintaining an RMSE of less than 3%, ranging from 2.21% to 2.90%. …”
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Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp.... by Mohd Shamzi Mohamed, Joo Shun Tan, Rosfarizan Mohamad, Mohd Noriznan Mokhtar, Arbakariya B. Ariff

“…RSM capability was also weighed against an artificial neural network (ANN) approach for predicting a composition that would result in maximum lipid productivity, Prlipid. …”
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Performance analysis of K-nearest neighbor, support vector machine, and artificial neural network classifiers for driver drowsiness detection with different road geometries by Zhenlong Li, Qingzhou Zhang, Xiaohua Zhao

“…Third, the performance of K-nearest neighbor, support vector machine, and artificial neural network classifiers were compared and evaluated. …”
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Investigating continuous intention to use metaverse in higher education institutions: a dual-staged structural equation modeling-artificial neural network approach by Reham Adel Ali, Mohamed Soliman, Muhammad Roflee Weahama, Muhammadafeefee Assalihee, Imran Mahmud

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