Enhancing prediction of wildfire occurrence and behavior in Alaska using spatio-temporal clustering and ensemble machine learning by A. Ahajjam, M. Allgaier, R. Chance, E. Chukwuemeka, J. Putkonen, T. Pasch

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PseudoCell: Hard Negative Mining as Pseudo Labeling for Deep Learning-Based Centroblast Cell Detection by Narongrid Seesawad, Piyalitt Ittichaiwong, Thapanun Sudhawiyangkul, Phattarapong Sawangjai, Peti Thuwajit, Paisarn Boonsakan, Supasan Sripodok, Kanyakorn Veerakanjana, Komgrid Charngkaew, Ananya Pongpaibul, Napat Angkathunyakul, Narit Hnoohom, Sumeth Yuenyong, Chanitra Thuwajit, Theerawit Wilaiprasitporn

“…<italic>Background:</italic> Deep learning models for patch classification in whole-slide images (WSIs) have shown promise in assisting follicular lymphoma grading. …”
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Leveraging machine learning to uncover multi-pathogen infection dynamics across co-distributed frog families by Daniele L. F. Wiley, Kadie N. Omlor, Ariadna S. Torres López, Celina M. Eberle, Anna E. Savage, Matthew S. Atkinson, Lisa N. Barrow

“…In this study, we leverage frozen tissues stored in natural history collections and machine learning techniques to characterize infection dynamics of three generalist pathogens known to cause mortality in frogs. …”
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Deep learning detects entire multiple-size lunar craters driven by elevation data and topographic knowledge by Liyang Xiong, Yanxiang Wang, Haoyu Cao, Yingchao Ren, Sijin Li, Yang Chen, Guoan Tang

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Trends and collaborations in case-based learning for online health education: a bibliometric analysis (2014-2024) by Agung Budiawan, Murti Kusuma Wirasti, Dwi Kusumawardani

Subjects: “…online course, case based learning, bibliometric…”
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Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data by Mihkel Kotli, Geven Piir, Uko Maran

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Hierarchical deep learning framework for automated marine vegetation and fauna analysis using ROV video data by Bjørn Christian Weinbach, Rajendra Akerkar, Marianne Nilsen, Reza Arghandeh

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Improving early prediction of crop yield in Spanish olive groves using satellite imagery and machine learning by M. Isabel Ramos, Juan J. Cubillas, Ruth M. Córdoba, Lidia M. Ortega

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Prediction of buckling damage of steel equal angle structural members using hybrid machine learning techniques by Nang Xuan Ho, Tien-Thinh Le, The-Hung Dinh, Van-Hai Nguyen

“…Abstract This article deals with prediction of buckling damage of steel equal angle structural members using a surrogate model combining machine learning and metaheuristic optimization technique. …”
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Logs for acid-base chemistry: illustrating the potential of multidisciplinary learning support interventions from the third space by Joshua Wang, Elise Kenny

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Stress and Coping Strategies of Madrasah’s Teachers on Applying Distance Learning During COVID-19 Pandemic in Indonesia by Siti Muawanah, Umi Muzayanah, Moses G. R. Pandin, Mochamad D. S. Alam, Januari P. N. Trisnaningtyas

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Prediction of stunting and its socioeconomic determinants among adolescent girls in Ethiopia using machine learning algorithms. by Alemu Birara Zemariam, Biruk Beletew Abate, Addis Wondmagegn Alamaw, Eyob Shitie Lake, Gizachew Yilak, Mulat Ayele, Befkad Derese Tilahun, Habtamu Setegn Ngusie

“…Therefore, this study aimed to employ multiple machine learning algorithms to identify the most effective model for the prediction of stunting among adolescent girls in Ethiopia.…”
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Design of the Inhibitors for Pseudorabies Virus Replication by Reinforcement Learning from HSV‑1 DNA Polymerase Inhibitors by Lin Wei, Yang Hu, Licheng Bai, Chenxu Xiao, Zhang Liu, Yun You, Keke Wang, Yunyuan Huang, Junfei Zhu, Jun Weng, Wenling Zhou, Han Li, Honghe Zhao, Zhiyong Wu, Meng Mei, Zigong Wei

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Measuring the Impact on Human Emotion When Listening and Reciting the Quran using AI/Machine Learning Techniques by Nur Asyiqin Hamzah, Hadhrami Ab Ghanni, Azlan Abd Aziz, Nur Hasanah Ali, Noor Zielah Abd Rahman

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Zonation system in admission of new student at state secondary school in Indonesia: how predictable to learning success by B. Bulkani, M. Fatchurahman, M. A. Setiawan

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Use of Machine Learning Models for Prediction of Organic Carbon and Nitrogen in Soil from Hyperspectral Imagery in Laboratory by Manuela Ortega Monsalve, Mario Cerón-Muñoz, Luis Galeano-Vasco, Marisol Medina-Sierra

“…The results show that machine learning models are a good alternative for analysing soil-related variables.…”
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Doctoral training at the University of Medical Sciences of Cienfuegos using distance learning methods, in the days of COVID-19 by Miriam Iglesias León, Norma Mur Villar, Manuel Cortés Cortés, José Aurelio Diaz Quiñones, Maria Aurelia San Juan Bosch

“…<br /><strong>Results:</strong> it was evidenced that distant learning methods used originate a wide range of possibilities in the teaching / learning processes as technological artifacts of scientific production with high communicative and interactive potential.…”
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Dust Storm Attenuation Prediction Using a Hybrid Machine Learning Model Based on Measurements in Sudan by Elfatih A. A. Elsheikh, E. I. Eltahir, Abdulkadir Tasdelen, Mosab Hamdan, Md Rafiqul Islam, Mohamed Hadi Habaebi, Aisha H. Abdullah Hashim

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Performance Evaluation of Deep Learning Image Classification Modules in the MUN-ABSAI Ice Risk Management Architecture by Ravindu G. Thalagala, Oscar De Silva, Dan Oldford, David Molyneux

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Long-Term Predictive Modelling of the Craniofacial Complex Using Machine Learning on 2D Cephalometric Radiographs by Michael Myers, Michael D. Brown, Sarkhan Badirli, George J. Eckert, Diane Helen-Marie Johnson, Hakan Turkkahraman

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