Quantitative Analysis of the Labeling Quality of Biological Images for Semantic Segmentation Based on Attribute Agreement Analysis by Rong Xiang, Xinyu Yuan, Yi Zhang, Xiaomin Zhang

“…This method evaluates labeling variation, including internal, external, and overall labeling quality, and labeling bias between labeling results and standards through case studies of tomato stem and group-reared pig images, which vary in labeling complexity. The process involves the following three steps: confusion matrix calculation, Kappa value determination, and labeling quality assessment. …”
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PMCT-based metric analysis of the first lumbar vertebra for estimation of sex and age in a North Indian population by Surya Kiran Panga, Taher Hussain, Pooja Gupta, Jay Narayan Pandit, Abhishek Yadav, Sudhir Kumar Gupta

“…Abstract Background Post-mortem computed tomography (PMCT) enables extensive skeletal morphometric data collection, facilitating the development of novel osteological identification methods. …”
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Smart Bio-Nanocoatings with Simple Post-Synthesis Reversible Adjustment by Mikhail Kryuchkov, Zhehui Wang, Jana Valnohova, Vladimir Savitsky, Mirza Karamehmedović, Marc Jobin, Vladimir L. Katanaev

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Memory Effect of Bacteria‐Killing Properties of Piezo‐Catalysts Nanomaterials through Defect Engineering by Omid Amiri, Karzan A. Qurbani, Karukh A. Babakr, Peshang Kh. Omer, L. Jay Guo, Hastyar Hama Rashid Najmuldeen, Martin Bertau, Peshawa H. Mahmood, Sangar S. Ahmed, Mohammed A. Jamal

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Enhanced diabetes prediction using skip-gated recurrent unit with gradient clipping approach by Suhas Kamshetty Chinnababu, Suhas Kamshetty Chinnababu, Suhas Kamshetty Chinnababu, Ananda Babu Jayachandra, Ananda Babu Jayachandra, Swathi Holalu Yogesh, Swathi Holalu Yogesh, Mohamed Abouhawwash, Mohamed Abouhawwash, Doaa Sami Khafaga, Eman Abdullah Aldakheel, Vinaykumar Vajjanakurike Nagaraju, Vinaykumar Vajjanakurike Nagaraju

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Oxygen effect on the performance of β-Ga2O3 enhancement mode MOSFETs heteroepitaxially grown on a sapphire by Yueh-Han Chuang, Fu-Gow Tarntair, Tzu-Wei Wang, Anoop Kumar Singh, Po-Liang Liu, Dong-Sing Wuu, Hao-Chung Kuo, Xiuling Li, Ray-Hua Horng

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Development of an artificial intelligence-based application for the diagnosis of sarcopenia: a retrospective cohort study using the health examination dataset by Chang-Won Jeong, Dong-Wook Lim, Si-Hyeong Noh, Sung Hyun Lee, Chul Park

“…However, these techniques have either been time-consuming or have required separate calculation processes after collecting each parameter. To address this gap, we propose an artificial intelligence (AI)-based web application that automates the collection of data, classification of the lumbar spine 3 (L3) slices, segmentation of the subcutaneous fat, visceral fat, and muscle areas in the classified L3 slices, and quantitative analysis of the segmented areas. …”
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Fine-Tuning BiomedBERT with LoRA and Pseudo-Labeling for Accurate Drug–Drug Interactions Classification by Ioan-Flaviu Gheorghita, Vlad-Ioan Bocanet, Laszlo Barna Iantovics

“…A checkpointing system saves predictions and confidence scores in small pieces, which means that the process can be continued and is not affected by system crashes. …”
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Paraneoplastic limbic encephalitis in a patient with small cell lung cancer. Case report by Nikolai A. Ognerubov, Olga O. Mirsalimova, Mikhail A. Zemur

“…The presence of antineuronal antibodies in serum and cerebrospinal fluid confirms the autoimmune (paraneoplastic) nature of the process.…”
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L-ENet: An Ultralightweight SAR Image Detection Network by Yutong Wang, Min Miao, Shiliang Zhu

“…This convolution module integrates the Ghost and efficient channel attention mechanisms, aiming to mitigate potential accuracy loss during the lightweight process. Furthermore, this study introduces a novel multiscale fusion pathway and a Concat module with adaptive weights to better harmonize semantic and detail information. …”
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An improved lightweight tongue segmentation model with self-attention parallel network and progressive upsampling by Xuan Wang, Yifang Cao, Yijia Chen, Huixia Li, Aiqing Han, Yan Tang

“…The model incorporates three key enhancements: (1) the adoption of a Self-Attention Parallel Network that integrates the self-attention mechanism and residual modules to achieve simultaneous extraction of local and global features; (2) the integration of the Efficient Channel Attention(ECA) mechanism into the Mix-FFN component to enhance feature extraction efficiency; and (3) the utilization of Multi-dimensional Feature Progressive Upsampling to mitigate precision loss during the upsampling process. Evaluation results on the BioHit public dataset demonstrate that, compared to the original Segformer, PAPU_TonSeg achieves improvements of 2.42% in Mean Pixel Accuracy (MPA), 0.78% in Mean Intersection over Union (MIoU), and 2.02% in the Dice coefficient, while boasting a lower parameter count and computational complexity. …”
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Benchmarking Variants of Recursive Feature Elimination: Insights from Predictive Tasks in Education and Healthcare by Okan Bulut, Bin Tan, Elisabetta Mazzullo, Ali Syed

“…To help researchers better understand and apply RFE more effectively, this study organizes existing variants into four methodological categories: (1) integration with different machine learning models, (2) combinations of multiple feature importance metrics, (3) modifications to the original RFE process, and (4) hybridization with other feature selection or dimensionality reduction techniques. …”
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Barlow Twins deep neural network for advanced 1D drug–target interaction prediction by Maximilian G. Schuh, Davide Boldini, Annkathrin I. Bohne, Stephan A. Sieber

“…By reducing time and cost, machine learning and deep learning can accelerate this laborious discovery process. In a novel approach, BarlowDTI, we utilise the powerful Barlow Twins architecture for feature-extraction while considering the structure of the target protein. …”
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FWFA: Fairness-Weighted Federated Aggregation for Privacy-Aware Decision Intelligence by Rahul Haripriya, Nilay Khare, Manish Pandey, Shrijal Patel, Jaytrilok Choudhary, Dhirendra Pratap Singh, Surendra Solanki, Duansh Sharma

“…This study introduces a novel federated learning framework, Fairness-Weighted Federated Aggregation (FWFA), which integrates fairness-aware weighting into the model aggregation process. Each client’s contribution is scaled using a fairness score computed from key metrics Demographic Parity (DP), Statistical Parity Difference (SPD), and Disparate Impact Ratio (DIR). …”
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A Temporal-Spectral Fused and Attention-Based Deep Model for Automatic Sleep Staging by Guidan Fu, Yueying Zhou, Peiliang Gong, Pengpai Wang, Wei Shao, Daoqiang Zhang

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Thermodynamic Modeling of Hashtag Dynamics for Social Media Clustering: A Maxwell-Boltzmann Approach by Krishnan Batri, Rajermani Thinakaran, Bhuvana Jayabalan, L. Karthikeyan, S. Lakshmi, R. Sowrirajan, Sivaram Murugan

“…This paper presents a novel thermodynamic framework that conceptualizes social network activity as system “temperature”, applying statistical mechanics principles to model hashtag importance as process innovation. We establish mathematical foundations based on the Maxwell-Boltzmann distribution, providing an information-theoretic justification for dynamic hashtag weighting. …”
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Optimal Power Flow for High Spatial and Temporal Resolution Power Systems with High Renewable Energy Penetration Using Multi-Agent Deep Reinforcement Learning by Liangcai Zhou, Long Huo, Linlin Liu, Hao Xu, Rui Chen, Xin Chen

“…Furthermore, the proposed DRL model significantly accelerates computation, achieving up to 85 times faster processing than MATPOWER.…”
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Scatter Search for Optimal Sizing of a Hybrid Renewable Energy System for Scheduling Green Hydrogen Production by Andrés Cacereño, Begoña González Landín, Antonio Pulido, Gabriel Winter, José Andrés Moreno

“…At present, energy demands are mainly covered by the use of fossil fuels. The process of fossil fuel production increases pollution from oil extraction, transport to processing centers, treatment to obtain lighter fractions, and delivery and use by the final consumers. …”
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Teaching Data Analysis and Machine Learning at University: Generalization of Experience and Perspectives by Victoria Dorofeeva, Sergey Stroev, Dmitrii Dorofeev

“…The work substantiates the conclusion about the relevance of training professional personnel who can be involved in the implementation of the national project “Digital Technologies”, in particular, as specialists in the field of technologies related to data analysis, big data processing and machine learning. Obviously, it is especially important to study technologies related to data analysis, big data processing and machine learning for students of physics, mathematics and IT training. …”
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Pitik: A Cebuano-Binisaya Intent-Based Chatbot for Cardiovascular Disease Patient Profiling and Risk Factor Recommendations by Joseph Cedeño, Andrew Manteza, Nicole Nacar, Merhamdin Umbukan, Cherrie Muaña, Ma. Juliet Vasay-Cruz, Ceasar Ian Benablo, Kristine Mae Adlaon

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