High-Dimensional Projected Clustering for Learner Competency Analysis in Medical Training Programs by Sandhya Harikumar, C. S. Jayamohan Pillai, V. Vani Chithra, Raghu Raman, Mr Kaimal, Kai-Yu Tang, Prema Nedungadi

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Similarity measure for intuitionistic fuzzy sets and its applications in pattern recognition and multimodal medical image fusion by Anjali Patel, Deepa Gupta, E. A. Gopalakrishnan, Divya Sasidharan, V. Sowmya, Mohammed Zakariah, Abdulaziz S. Almazyad

“…Then, we use the proposed IFSM to extract the features of base subimages and define two fusion rules to fuse the base subimages and detailed subimages. …”
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Efficacy of Mepolizumab in the Treatment of Severe Asthma with a Mixed Granulocytic Pattern of Airway Inflammation (Case Report) by A. M. Gubareva, S. V. Fedosenko, D. A. Vinokurova, S. V. Nesterovich, E. S. Kulikov, D. V. Polyakova, E. A. Starovoitova

“…The most common mixed granulocytic pattern of severe asthma occurs in comorbid pathology, in particular, when it is combined with chronic obstructive pulmonary disease (COPD) or bronchiectasis.In the presented observations, both patients had an experience of smoking, a late manifestation of bronchial asthma with the development of centrilobular emphysema and an irreversible decrease in the FEV/FVC ratio as part of the development of COPD. …”
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Discovering the key symptoms for identifying patterns in functional dyspepsia patients: A doctor's decision and machine learning by Da-Eun Yoon, Heeyoung Moon, In-Seon Lee, Younbyoung Chae

“…Our findings suggest that these approaches may contribute to enhancing accuracy and reliability in the development of pattern identification tools.…”
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Cross-User Electromyography Pattern Recognition Based on a Novel Spatial-Temporal Graph Convolutional Network by Mengjuan Xu, Xiang Chen, Yuwen Ruan, Xu Zhang

“…With the goal of promoting the development of myoelectric control technology, this paper focuses on exploring graph neural network (GNN) based robust electromyography (EMG) pattern recognition solutions. …”
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Bibliometric analysis of current trends and emerging patterns in the application of nanomaterials for non-small cell lung cancer by Shanshan Cai, Weichang Yang, Hongquan Xing, Jiale Yang, Hongdan Luo, Xiaoqun Ye

“…We characterized the publication patterns, pinpointed the most influential nations, institutions, authors, journals, and hot topics related to nanomaterial applications in NSCLC, and proposed potential avenues for future development.…”
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Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy by Jing Zhang, Lulu Cheng, Shan Jiang, Duosheng Zhu

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Sleep problems and sensory features in children with low-average cognitive abilities and autism spectrum disorder by Sumie Iwasaki, Yuko Yoshimura, Chiaki Hasegawa, Sanae Tanaka, Takashi Ikeda, Ken Yaoi, Tetsu Hirosawa, Mitsuru Kikuchi

“…Abstract Children with Autism Spectrum Disorder (ASD) often have more sleep disturbances than typically developing children. These sleep disturbances have been suggested to be associated with atypical sensory features in children with ASD. …”
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Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network by Ge Gao, Xu Zhang, Xiang Chen, Zhang Chen

“…The objective of this work is to develop a novel myoelectric pattern recognition (MPR) method to mitigate the concurrent interference of electrode shift and loosening, thereby improving the practicality of MPR-based gestural interfaces towards intelligent control. …”
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Modeling inter-city population flows: a Deep Radiation model with multisource geographic features by Jingjing Liu, Lei Xu, Le Ma, Chao Wang, Nengcheng Chen

“…By replacing linear equations with a feedforward neural network, our model predicts migration flows based on an expanded set of features across four dimensions: economic development, urbanization, infrastructure, and environmental factors. …”
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Modulation pattern recognition method of wireless communication automatic system based on IABLN algorithm in intelligent system. by Ting Xie, Xing Han

“…The aim of this study is to address the limitations of convolutional networks in recognizing modulation patterns. These networks are unable to utilize temporal information effectively for feature extraction and modulation pattern recognition, resulting in inefficient modulation pattern recognition. …”
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Research prevalence of psoriasis in countries and Ukraine by А. А. Kotvitska, V. V. Carlo

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LRU-Net: lightweight and multiscale feature extraction for localization of ACL tears region in MRI images by Xiaojun Si, Liang Yan, Cui Shi, Yang Xu

“…Furthermore, it employs a dynamic feature extraction module for adaptive multiscale feature extraction. …”
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Deep Learning Model for Feature Extraction and Anomaly Recognition in High-Dimensional Energy Metering Data by Huakun Que, Zetao Jiang, Zhifeng Zhou, Yongsheng He, Xin Liu

“…Methods: High-dimensional metering data from a city energy provider is processed using a Convolutional Autoencoder (CAE) to extract deep features and reduce dimensionality. These features are then fed into a Cascaded Long Short-Term Memory (CLSTM) network, which identifies anomalous patterns in the data. …”
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Structure-Activity Relationships in Alkoxylated Resorcinarenes: Synthesis, Structural Features, and Bacterial Biofilm-Modulating Properties by Mariusz Urbaniak, Łukasz Lechowicz, Barbara Gawdzik, Maciej Hodorowicz, Ewelina Wielgus

“…In contrast, compound <b>2e</b> and the DMSO control exhibited minimal impact on biofilm development. The results suggest that specific structural features of the alkoxy chains may modulate microbial responses, potentially via membrane stress or quorum sensing interference. …”
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Visualizing Relaxation in Wearables: Multi-Domain Feature Fusion of HRV Using Fuzzy Recurrence Plots by Puneet Arya, Mandeep Singh, Mandeep Singh

“…Among six evaluated classifiers, support vector machine (SVM) achieved the highest performance, with 96.6% accuracy and 100% specificity using only three selected features. Our approach offers both human-interpretable visual feedback through FRP and accurate automated detection, making it highly promising for objectively monitoring real-time stress and developing biofeedback systems in wearable devices.…”
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Predicting drug-target interactions using machine learning with improved data balancing and feature engineering by Md. Alamin Talukder, Mohsin Kazi, Ammar Alazab

“…The framework leverages comprehensive feature engineering, utilizing MACCS keys to extract structural drug features and amino acid/dipeptide compositions to represent target biomolecular properties. …”
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Mapping Disorders with Neurological Features Through Mitochondrial Impairment Pathways: Insights from Genetic Evidence by Anna Makridou, Evangelie Sintou, Sofia Chatzianagnosti, Iasonas Dermitzakis, Sofia Gargani, Maria Eleni Manthou, Paschalis Theotokis

“…Genetic, clinical and molecular data were analyzed to elucidate shared and distinct pathophysiological features. A comprehensive table synthesizes genetic causes, inheritance patterns, and neurological manifestations across disorders. …”
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Drug History and SLE Laboratory Findings Among Iraqi Patients: A Hospital‐Based Study by Hashim Talib Hashim, Ahmed Dheyaa Al‐Obaidi, Mustafa Najah Al‐Obaidi, Hossam Tharwat Ali, Idris Sula, Hozifa Alfaki, Abdelrahim Elamin, Alaa Hamza Hermis, Assalah Othman, Ahmed Qasim Mohammed Alhatemi

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Pore–Fracture Structure and Fractal Features of Carboniferous Taiyuan Formation Hydrocarbon Source Rocks as Investigated Using MICP, LFNMR, and FESEM by Dun Wu, Liu Zhao, Guangqing Hu, Wenyong Zhang

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