Biomarker identification and gene-drug interaction prediction for breast cancer using machine learning algorithms by Raja Abhavya, Pragya Pragya, Sabitha R., Kumar Brijesh, Agastinose Ronickom Jac Fredo

“…The present study emphasizes the significance of utilizing genetic data and powerful machine learning algorithms to decipher the intricacies of BC biology and expedite the creation of tailored therapeutic approaches.…”
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Integrating recursive feature selection with automated machine learning framework for global wheat price prediction by Prity Kumari, N. Harshith, Athula Ginige

“…Wheat price forecasting is challenging due to the interplay between economic trends, environmental variability and unpredictable market conditions, as well as the scarcity of reliable data. This research presents an innovative method for predicting global wheat prices by combining Recursive Feature Elimination with Cross Validation (RFECV) and Bayesian Ridge Regression in an Automated Machine Learning (AutoML) framework. …”
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AI Knows Aesthetics: AI-Generated Interior Design Identification Using Deep Learning Algorithms by Fei Liu, Kailing Deng

“…However, recent advancements in deep learning, including hybrid AI models and transformer-based vision networks, have further enhanced classification accuracy by integrating multimodal learning techniques. …”
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Unmanned Aerial Vehicle Path Planning in Complex Dynamic Environments Based on Deep Reinforcement Learning by Jiandong Liu, Wei Luo, Guoqing Zhang, Ruihao Li

“…In this paper, an enhanced deep reinforcement learning approach is presented for unmanned aerial vehicles (UAVs) operating in dynamic and potentially hazardous environments. …”
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SECURITY ASSESSMENT OF MOODLE-BASED DISTANCE LEARNING SYSTEM COMPONENTS USING STATIC ANALYSIS TOOLS by Vladislav K. Kuchmin, Grigory O. Krylov

“…The article presents a methodological approach to assessing the security of software components within the Moodle-based distance learning system using automated static source code analysis methods. …”
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The role of parental involvement and mathematics self-concept of elementary school students in online mathematics learning by Y. W. Purnomo, N. Apriyanti, S. A. Mubarokah, . Susilowati, W. A. Anggraheni

“…Introduction. Learning mathematics from home during the COVID-19 pandemic is a challenge for both parents and students to manage to engage in learning. …”
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Trainee growth vs. fixed mindset in clinical learning environments: enhancing, hindering and goldilocks factors by Samantha Rae Hopkins, Valerie Isobel Rae, Samantha E. Smith, Victoria R. Tallentire

“…How growth mindset might be promoted within the clinical learning environment is underexplored. This study aimed to explore the factors promoting a growth mindset versus fixed mindset in trainees from the perspective of the trainees. …”
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Machine Learning-Based Mooring Failure Detection for FPSOs: A Two-Step ANN Approach by Omar Jebari, Do-Soo Kwon, Sung-Jae Kim, Chungkuk Jin, Moohyun Kim

“…This study presents a two-step artificial neural network (ANN) approach for detecting mooring failures in a spread-moored floating production storage and offloading (FPSO) vessel using platform motion data. …”
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Towards a Framework for Acquisition and Analysis of Speeches to Identify Suspicious Contents through Machine Learning by Md. Rashadur Rahman, Mohammad Shamsul Arefin, Md. Billal Hossain, Mohammad Ashfak Habib, A. S. M. Kayes

“…The experimental results show that our proposed deep learning-based model provides the highest accuracy compared to other algorithms.…”
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MSNet: A Novel Deep Learning Framework for Efficient Missing Seedling Detection in Maize Fields by Yong Shi, Ruijie Xu, Zhiquan Qi

“…We present SeedNet, a detector that leverages row direction information to enhance small seedling detection performance. …”
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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…To address these limitations, we developed a machine learning (ML) framework that automates the selection of optimal docking parameters. …”
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A novel neuroimaging based early detection framework for alzheimer disease using deep learning by Areej Alasiry, Khlood Shinan, Abeer Abdullah Alsadhan, Hanan E. Alhazmi, Fatmah Alanazi, M. Usman Ashraf, Taseer Muhammad

“…Accurate early detection is critical for effective intervention. This study presents Neuroimaging-based Early Detection of Alzheimer’s Disease using Deep Learning (NEDA-DL), a novel computer-aided diagnostic (CAD) framework leveraging a hybrid ResNet-50 and AlexNet architecture optimized with CUDA-based parallel processing. …”
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Reinforcement Learning-Based Formulations With Hamiltonian-Inspired Loss Functions for Combinatorial Optimization Over Graphs by Redwan Ahmed Rizvee, Raheeb Hassan, Md. Mosaddek Khan

“…In this paper, firstly, we identify the limitations and empirically present our strategy to improve PI-GNN’s performance. …”
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Generative Deep Learning Design of Single-Domain Antibodies Against Venezuelan Equine Encephalitis Virus by Jinny L. Liu, Gabrielle C. Bayacal, Jerome Anthony E. Alvarez, Lisa C. Shriver-Lake, Ellen R. Goldman, Scott N. Dean

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A Novel Machine Learning-based Diagnostic Algorithm for Detection of Onychomycosis through Nail Appearance by Serkan Düzayak, Muhammed Kürşad Uçar

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A Novel Multimodal Deep Learning Approach With Loss Function for Detection of Sleep Apnea Events by Alireza Fakhim Babaei, Jafar Tanha, Mohammad Ali Balafar, Seyedehsan Roshan

“…In this study, we propose a novel deep-learning approach for automatic sleep apnea detection using physiological signals. …”
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Training in self-regulated learning based on a neuropsychological approach to academic stress in university students by Diego Daniel Díaz Guerra, Marena de la C Hernández Lugo, María del Pilar Fernández Celis, Raquel Yovana Tello Flores, Esteban Rodríguez Torres

“…Introduction: academic stress is a common challenge among university students and can have negative effects on their performance and well-being, as well as hinder conscious learning regulation. This article presents a training program designed to address this problem from a neuropsychological approach and promote self-regulated learning. …”
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Prediction of InSAR deformation time-series using improved LSTM deep learning model by Rupika Soni, Mohammad Soyeb Alam, Gajendra K. Vishwakarma

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Ethnic Chinese during the New Order: Teaching Materials Development for History Learning based on Multiculturalism by Hendra Kurniawan

“…The history of Indonesian Chinese society is still rarely studied in history learning at school. One of them concerns the discriminatory treatment of them during the New Order era. …”
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Utilization of Ensemble Techniques in Machine Learning to Predict the Porosity and Hardness of Plasma-Sprayed Ceramic Coating by N. Radhika, M. Sabarinathan, S. Sivaraman

“…To address this challenge, the present study employs advanced machine learning ensemble techniques, including bagging, boosting, stacking, weighted averaging, voting, and hybrid methods, to accurately predict the porosity and hardness of plasma-sprayed ceramic coatings based on key process parameters. …”
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