High-throughput mesoscopic optical imaging data processing and parsing using differential-guided filtered neural networks by Hong Zhang, Zhikang Lu, Peicong Gong, Shilong Zhang, Xiaoquan Yang, Xiangning Li, Zhao Feng, Anan Li, Chi Xiao

“…Building on the segmentation, we utilize connectivity analysis for ascertaining three-dimensional spatial orientation of each brain within the array. …”
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Recurrent Neural Network Optimized by Grasshopper for Accurate Audio Data-Based Diagnosis of Parkinson's Disease by Saif Wali Ali Alsudani, Ghassan Khudair Saud

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Feature Selection for Hypertension Risk Prediction Using XGBoost on Single Nucleotide Polymorphism Data by Lailil Muflikhah, Tirana Noor Fatyanosa, Nashi Widodo, Rizal Setya Perdana, Solimun, Hana Ratnawati

“…The high dimensionality of SNP data was effectively managed to identify significant features as biomarkers using the XGBoost feature selection method. …”
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Subsurface Geosciences Learning in Virtual Reality: A Case Study in Central Luconia Province, Malaysia by Grisel Jiménez, Abdul Halim Latiff, Katja Schulze

“…It includes a post-stacked time- 3D seismic cube linked to wells, allowing students to work with seismic data, adjust scales, and conduct preliminary seismic analysis. …”
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Fusing LiDAR and Photogrammetry for Accurate 3D Data: A Hybrid Approach by Rytis Maskeliūnas, Sarmad Maqsood, Mantas Vaškevičius, Julius Gelšvartas

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Machine Learning for Blockchain and IoT Systems in Smart Cities: A Survey by Elias Dritsas, Maria Trigka

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Resilience evaluation of memristor based PUF against machine learning attacks by Hebatallah M. Ibrahim, Heorhii Skovorodnikov, Hoda Alkhzaimi

“…Our study focuses on building a machine learning analysis and attack framework of tools on $$Cu/HfO_{2-x}/p^{++}Si$$ C u / H f O 2 - x / p + + S i memristor-based PUF (MR-PUF). …”
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Automatic Feature Selection for Imbalanced Echocardiogram Data Using Event-Based Self-Similarity by Huang-Nan Huang, Hong-Min Chen, Wei-Wen Lin, Rita Wiryasaputra, Yung-Cheng Chen, Yu-Huei Wang, Chao-Tung Yang

“…<b>Conclusions:</b> Our findings highlight the potential of machine learning-driven echocardiogram analysis to enhance patient care by providing accurate, data-driven assessments.…”
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Predictive analytics technique based on hybrid sampling to manage unbalanced data in smart cities by Ayushi Chahal, Preeti Gulia, Nasib Singh Gill, Mohammad Yahya, Mohd Anul Haq, Mohammed Aleisa, Abdullah Alenizi, Arfat Ahmad Khan, Piyush Kumar Shukla

“…This paper proposes a novel predictive analytical technique to manage unbalanced data. A pipeline is designed using Principal Component Analysis (PCA), a hybrid sampling method, and a Machine Learning (ML) prediction method. …”
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Synergistic review of automation impact of big data, AI, and ML in current data transformative era [version 2; peer review: 2 approved, 1 approved with reservations] by Siddharth Swarup Rautaray, Manjusha Pandey, Swastik Rath

“…The convergence of automation, big data analytics (BDA), artificial intelligence (AI), and machine learning (ML) has ushered in a new era of technological advancement, reshaping industries, and societies worldwide. …”
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Pharmacovigilance in the digital age: gaining insight from social media data by Fan Dong, Wenjing Guo, Jie Liu, Tucker A. Patterson, Huixiao Hong

“…However, the unstructured nature of social media content presents challenges in data analysis, including variability and potential biases. …”
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Use of self-organizing maps for the classification of cardiometabolic risk and physical fitness in adolescents by Rodrigo Yáñez-Sepúlveda, Rodrigo Olivares, Camilo Ravelo, Guillermo Cortés-Roco, Juan Pablo Zavala-Crichton, Claudio Hinojosa-Torres, Josivaldo de Souza-Lima, Matías Monsalves-Álvarez, Tomás Reyes-Amigo, Juan Hurtado-Almonacid, Jacqueline Páez-Herrera, Sandra Mahecha-Matsudo, Jorge Olivares-Arancibia, Vicente Javier Clemente-Suárez

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Interactive Arabic E-Learning for Prospective Students Studying in the Middle East by Mohammad Zaelani Musonif, Hanik Mahliatussikah, Kholisin Kholisin

“… This research aimed to investigate the indicators in the analysis of needs for the development of Arabic language e-learning. …”
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Interactive Arabic E-Learning for Prospective Students Studying in the Middle East by Mohammad Zaelani Musonif, Hanik Mahliatussikah, Kholisin Kholisin

“… This research aimed to investigate the indicators in the analysis of needs for the development of Arabic language e-learning. …”
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Interactive Arabic E-Learning for Prospective Students Studying in the Middle East by Mohammad Zaelani Musonif, Hanik Mahliatussikah, Kholisin Kholisin

“… This research aimed to investigate the indicators in the analysis of needs for the development of Arabic language e-learning. …”
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Revolutionizing educational decision-making: a robust machine learning mechanism for predicting student performance by Muhammad Nadeem Gul, Waseem Abbasi, Muhammad Yaqoob Wani

“…Abstract Machine learning has become an essential component across various domains, including the education sector. …”
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Matrix-based method to update incomplete multigranulation three-way regions with increasing objects by Chengxiang Hu, Haoran Zhang, Xingpeng Kuai, Xiaoling Huang, Xiaojing Hu

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Representative Sample Size for Estimating Saturated Hydraulic Conductivity via Machine Learning: A Proof‐Of‐Concept Study by Amin Ahmadisharaf, Reza Nematirad, Sadra Sabouri, Yakov Pachepsky, Behzad Ghanbarian

“…For each subset, we conducted the learning curve analysis on the training and cross‐validation data sets. …”
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Inconsistency-driven approach for human-in-the-loop entity matching by Hiroyoshi Ito, Takahiro Koizumi, Ryuji Yoshimoto, Yukihiro Fukushima, Takashi Harada, Atsuyuki Morishima

“…Human-in-the-loop entity matching is a human-AI collaborative approach which is effective when the data for entity matching is incomplete or requires domain knowledge. …”
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Regression Analysis to Predict the Length of Time to Complete a Thesis based on the Title by Al Aminuddin, Rahmat Hidayat, Gita Sastria, Astried Astried

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