Personality predicts internalizing symptoms and quality of life in police cadets: a comparison of artificial intelligence and parametric approaches by Macià Buades-Rotger, Ana Martínez Catena, Guillermo Recio, Mireia Cano Gallent, Jordi Niñerola i Maymí, Anna Figueras Masip, David Gallardo-Pujol

“…Moreover, we compared seven popular artificial intelligence and linear regression models (Elastic Net, General Linear Model, Lasso Regression, Neural Networks, Random Forests, and Support Vector Regression) in predicting MHRQoL as a function of all other variables. …”
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Artificial intelligence approach to magnetohydrodynamic flow of non-Newtonian fluids over a wedge: Thermophoresis and Brownian motion effects by Talal Taha, Sohaib Abdal, Liaqat Ali, Rana Muhammad Zulqarnain, Se-Jin Yook

“…Further optimization and simplification of the analysis are achieved by using an artificial neural networking base Levenberg Marquardt algorithm (ANN-LMA) model. …”
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Tree networks of real-world data: Analysis of efficiency and spatiotemporal scales by Davide Cipollini, Lambert Schomaker

“…Hierarchical tree structures are common in many real-world systems, from tree roots and branches to neuronal dendrites and biologically inspired artificial neural networks, as well as in technological networks for organizing and searching complex datasets of high-dimensional patterns. …”
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Crack-ConvT Net: A Convolutional Transformer Network for Crack Segmentation in Underwater Dams by Pengfei Shi, Hongzhu Chen, Zaiming Geng, Xinnan Fan, Yuanxue Xin

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High-fidelity EEG feature-engineered taxonomy for bruxism and PLMS prognostication through pioneering and avant-garde ML frameworks by Shivam Tiwari, Deepak Arora, Barkha Bhardwaj

“…Using K-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), and Support Vector Machines (SVM) with Radial Basis Function (RBF), Bruxism categorization was accomplished. …”
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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer by Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco

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Decoding Schizophrenia: How AI-Enhanced fMRI Unlocks New Pathways for Precision Psychiatry by Valeria Di Stefano, Martina D’Angelo, Francesco Monaco, Annarita Vignapiano, Vassilis Martiadis, Eugenia Barone, Michele Fornaro, Luca Steardo, Marco Solmi, Mirko Manchia, Luca Steardo

“…This manuscript explores how the integration of these technologies has unveiled key insights into schizophrenia’s structural and functional neural anomalies. fMRI research highlights disruptions in crucial brain regions like the prefrontal cortex and hippocampus, alongside impaired connectivity within networks such as the default mode network (DMN). …”
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Criminal Law Challenged by Crossing into Virtual Reality by Mahdi Karimi

“…It should be noted that* the current criminal policy approach requires re-evaluation and reassessment in line with the current advancement of neural technologies and artificial intelligence to effectively monitor and address the challenges and consequences arising from the development of these technologies. …”
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Classifying kidney disease using a dense layers deep learning model by Amal Al-Rasheed, Sheikh Muhammad Saqib, Muhammad Zubair Asghar, Tehseen Mazhar, Asim Seedahmed Ali Osman, Mohammad Shahid, Muhammad Iqbal, Muhammad Amir Khan

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Intelligent Dispatch Decision-Making for UHVDC Blocking Fault Based on Deep Learning by Xiaonan YANG, Bo SUN, Yansheng LANG

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Starch–Glycerol-Based Hydrogel Memristors for Bio-Inspired Auditory Neuron Applications by Jiachu Xie, Yuehang Ju, Zhenwei Zhang, Dianzhong Wen, Lu Wang

“…Against this backdrop, memristor devices, capable of mimicking the computational functions of brain neural networks, have emerged as key components in neuromorphic systems. …”
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Sunflower-based butterfly optimization algorithm with enhanced RNN for the harmonics elimination in multilevel inverter by V. Mohan, G. Krithiga, M. Thamil Alagan, V. Sathya

“…Enhanced Recurrent Neural Network (ERNN) shows a kind of recurrent neural network in which the hidden neurons are tweaked by SF-BOA with the goal of minimizing THD. …”
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Optimizing Renewable Energy Systems Placement Through Advanced Deep Learning and Evolutionary Algorithms by Konstantinos Stergiou, Theodoros Karakasidis

“…This study introduces GREENIA, a novel artificial intelligence (AI)-powered framework for optimizing RES placement that holistically integrates machine learning (gated recurrent unit neural networks with swish activation functions and attention layers), evolutionary optimization algorithms (Jaya), and Shapley additive explanations (SHAPs). …”
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Machine learning for active sites prediction of quinoline derivatives by Jie Sun, Zi-Hao Li, Yi-Fei Yang, Shu-Yu Zhang

“…In this study, a generalizable approach to predict site selectivity is accomplished by using artificial neural network (ANN), which is suitable for the site prediction of derivatives of quinoline. …”
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Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…For each rock class, we applied regression techniques—such as random forest (RF), k-nearest neighbors (k-NN), extreme gradient boosting (XGB), and artificial neural networks (ANN)—to estimate the logarithm of capillary pressure. …”
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Application of Fuzzy-RBF-CNN Ensemble Model for Short-Term Load Forecasting by Mohini Yadav, Majid Jamil, Mohammad Rizwan, Richa Kapoor

“…RBFNNs and CNNs are trained in two phases using the functional link artificial neural network (FLANN) optimization method with a deep learning structure. …”
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A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

“…To evaluate the proposed method, eight DL models — Feedforward Neural Network, Recurrent Neural Network, Deep Neural Network, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Bidirectional LSTM, Gated Recurrent Unit (GRU) and Bidirectional GRU were trained on selected features using different FS methods, as well as complete dataset. …”
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A blockchain based deep learning framework for a smart learning environment by Shimaa Ouf, Soha Ahmed, Yehia Helmy

“…Then apply the deep learning model to this secured data to predict the learner’s performance. The smart contract functions also play a role in enabling the university to issue learners’ certificates that are stored on the blockchain to be available and verifiable by all the nodes in the network. …”
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Single Gaussian Chaotic Neuron: Numerical Study and Implementation in an Embedded System by Luis M. Torres-Treviño, Angel Rodríguez-Liñán, Luis González-Estrada, Gustavo González-Sanmiguel

“…Artificial Gaussian neurons are very common structures of artificial neural networks like radial basis function. …”
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Analysis of entropy generation in tri-hybrid nanofluid flow towards a spinning disk under the influence of hall effect and variable viscosity by Moh Yaseen, Ritu Bartwal, Anum Shafiq, Sawan Kumar Rawat, Qasem M. Al-Mdallal, Umesh Khanduri, Tabassum Naz Sindhu

“…Subsequently, an advanced artificial neural network (ANN) is employed to predict the Nusselt number. …”
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