Application of neural architecture search in lithology identification by Yuhao Zhang, Hanmin Xiao, Meng Du, Qingjie Liu, Jingwei Tao, Yongcheng Luo, Li Peng, Jianbo Tan

“…Abstract Identifying rock types is the essential step in geological exploration because it guides reservoir description and development planning. …”
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Integrative multi-omics analysis and experimental validation identify molecular subtypes, prognostic signature, and CA9 as a therapeutic target in oral squamous cell carcinoma by Yun Zhao, Yun Zhao, Jing Yang, Yamei Jiang, Jingbiao Wu

“…The MSCC model, developed using the StepCox [both]+plsRcox algorithm, demonstrated superior prognostic performance compared to existing models. …”
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The usefulness of automated high frequency ultrasound image analysis in atopic dermatitis staging by Joanna Czajkowska, Adriana Polańska, Anna Slian, Aleksandra Dańczak-Pazdrowska

“…The fully automated image processing framework combines advanced machine learning techniques for fast, reliable, and repeatable HFUS image analysis, supporting clinical decisions. …”
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Non‐Invasive Diagnosis of Hypertrophic Cardiomyopathy by Breath by Yael Hershkovitz‐Pollak, Manhal Habib, Yoav Y. Broza, Olga Katz, Harry Rakowski, Hossam Haick

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Leveraging a Vision Transformer and Adversarial Unsupervised Domain Adaptation to Generate the NIR Band on Out-of-Domain VHR RGB by Viktoria Kristollari, Vassilia Karathanassi

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An Intelligent IoT and ML-Based Water Leakage Detection System by Mohammed Rezwanul Islam, Sami Azam, Bharanidharan Shanmugam, Deepika Mathur

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Recognizing American Sign Language gestures efficiently and accurately using a hybrid transformer model by Mohammed Aly, Islam S. Fathi

“…Overall, this work offers a practical and powerful solution for gesture recognition, striking an optimal balance between accuracy, speed, and efficiency—an important step toward real-world applications.…”
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PaleAle 6.0: Prediction of Protein Relative Solvent Accessibility by Leveraging Pre-Trained Language Models (PLMs) by Wafa Alanazi, Di Meng, Gianluca Pollastri

“…RSA prediction, especially when homology transfer cannot provide information about a protein’s structure, is a significant step toward addressing the protein structure prediction challenge. …”
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Moanna: Multi-Omics Autoencoder-Based Neural Network Algorithm for Predicting Breast Cancer Subtypes by Richard Lupat, Rashindrie Perera, Sherene Loi, Jason Li

“…Cancer subtyping delivers valuable insights into the study of cancer heterogeneity and fulfills an essential step toward personalized medicine. For example, studies in breast cancer have shown that cancer subtypes based on molecular differences are associated with different patient survival and treatment responses. …”
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Inklusiv-digitale Bildung im Studium zur Lehrkraft für Berufskunde im Hauptberuf: Analyse eines Interventionsprogramms by René Wüthrich

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Instantaneous Metabolic Energetics: Data-Driven Modeling Using Function-Based Surrogates and Gradient Boosting by Christopher Buglino, William Z. Peng, Stacy Ashlyn, Hyunjong Song, Howard J. Hillstrom, Joo H. Kim

“…A gradient-boosted machine-learning model was then trained on the surrogate functions’ outputs. …”
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Point-SPV: end-to-end enhancement of object recognition in simulated prosthetic vision using synthetic viewing points by Ashkan Nejad, Ashkan Nejad, Ashkan Nejad, Burcu Küçükoǧlu, Jaap de Ruyter van Steveninck, Sandra Bedrossian, Joost Heutink, Joost Heutink, Gera A. de Haan, Gera A. de Haan, Frans W. Cornelissen, Marcel van Gerven

“…In this paper, we introduce Point-SPV, an end-to-end deep learning model designed to enhance object recognition in simulated prosthetic vision. …”
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Cross-validation for training and testing co-occurrence network inference algorithms by Daniel Agyapong, Jeffrey Ryan Propster, Jane Marks, Toby Dylan Hocking

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Development and Validation of the Relational Tissue Altered (RTA) Index: Applied Artificial Intelligence for the Assessment of Structural Impact from Laser Vision Correction by Aydano P. Machado, Louise Pellegrino G. Esporcatte, Marcella Q. Salomão, Bernardo T. Lopes, João Marcelo A. G. Lyra, Renato Ambrósio

“…Methods An artificial intelligence-based machine learning approach was used to create a predictive model for the impact of corneal refractive surgery. …”
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Architecture and implementation of ulrb algorithm in R by Francisco Pascoal, Rodrigo Costa, Luís Torgo, Catarina Magalhães, Paula Branco

“…To solve this problem, we have proposed the utilization of unsupervised machine learning, through the ulrb (“Unsupervised Learning Definition of the Microbial Rare Biosphere”) algorithm, implemented as an R package (v0.1.8). …”
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An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival by Saima Kanwal, Muhammad Abdullah, Sahil Kumar, Saqib Arshad, Muhammad Shahroz, Dawei Zhang, Dileep Kumar

“…This study marks a significant step forward in climate-smart aquaculture, contributing to enhanced fish health, survival, and yield while mitigating the risks posed by climate change on aquatic ecosystems.…”
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YOLOv8-RD: High-Robust Pine Wilt Disease Detection Method Based on Residual Fuzzy YOLOv8 by Junchao Yuan, Lina Wang, Tingting Wang, Ali Kashif Bashir, Maryam M. Al Dabel, Jiaxing Wang, Hailin Feng, Kai Fang, Wei Wang

“…Simultaneously, we integrated a detail processing module into the ResFuzzy module to enhance the low-frequency detail features transmitted in residual learning. Furthermore, by incorporating the dynamic upsampling operator, our model can dynamically adjust the sampling step size based on the variations in the input feature map during the upsampling process, thereby effectively recovering detail from the feature map. …”
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Extracting individual trajectories from text by fusing large language models with diverse knowledge by Le Liu, Tao Pei, Zidong Fang, Xiaorui Yan, Chenglong Zheng, Xi Wang, Ci Song, Wenfei Luan, Jie Chen

“…To address these limitations, we propose T2TrajLLM, a novel framework that fuses LLMs with domain knowledge through three components: (1) a lightweight trajectory model for structured guidance, (2) a text-to-trajectory transformation model enabling multi-step reasoning, and (3) labelled text-trajectory samples for learning domain-adaptive constraint rules. …”
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Disease candidate genes prediction using positive labeled and unlabeled instances by Sepideh Molaei, Saeed Jalili

“…The second step is the learning of a binary model using causing genes of each disease as a positive learning set and the reliable negative genes extracted from that disease. …”
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USING TED TALKS IN TEACHING ENGLISH FOR SPECIFIC PURPOSES AT UNIVERSITY LEVEL by Vilkhovchenko Nadiia

“…The methodology of incorporating TED talks in the teaching process should involve a series of steps that aim to maximize effective learning outcomes. …”
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