Clinical features and outcomes of Rhegmatogenous Retinal Detachments in Acute Retinal Necrosis by Shabtab Nasir, Samreen Mehfooz, Soumyava Basu, Rajeev R. Pappuru, Mudit Tyagi

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Features of the Effect of Cataracts and Glaucoma on the Daily Activities of Patients with Sarcopenic Obesity by O. L. Fabrikantov, A. E. Kopylov, N. M. Agarkov

“…In particular, restrictions on threading a needle in patients with cataracts and sarcopenic obesity have 1.84 ± 0.03 points, which is significantly higher than in patients with glaucoma and sarcopenic obesity (p < 0.01). A similar pattern has been established for nail clipping, the limits for which are 1.75 ± 0.03 points and 1.43 ± 0.04 points, respectively. …”
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Patch-Based Texture Feature Extraction Towards Improved Clinical Task Performance by Tao Lian, Chunyan Deng, Qianjin Feng

“…Texture features can capture microstructural patterns and tissue heterogeneity, playing a pivotal role in medical image analysis. …”
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VCINet: Visual Cue-Inspired Feature Learning Network for SAR Building Segmentation by Mengyu Wang, Zhiyuan Yan, Wenhui Diao, Xudong Hu, Yingchao Feng, Linlin Xin, Junxi Li, Xian Sun

“…First, to improve intraclass variance and emphasize internal consistency, an elaborately designed pattern guidance module is introduced. We systematically study the stable spatial pattern of buildings and leverage the variogram function to model the characteristic to constrain deep network training. …”
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Ensemble learning techniques reveals multidimensional EEG feature alterations in pediatric schizophrenia by Ying Mao, Ying Mao, Fang Wang, Shan Wang, Zhaowei Wang, Gang Li, Xuchen Qi, Xuchen Qi, Yu Sun, Yu Sun

“…Schizophrenia (SCZ) is a severe mental disorder that impairs brain function and daily life, while its early and objective diagnosis remains a major clinical challenge due to the reliance on subjective assessments. This study aims to develop a machine learning-based framework for the auxiliary diagnosis of SCZ using multi-dimensional electroencephalogram (EEG) features and to investigate the underlying neural alterations. …”
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PFVnet, a feature enhancement network for low recognition coal and rock images by Cai Han, Zhenwen Liu, Shenglei Zhao, Yubo Li, Yanwei Duan, Xinzhou Yang, Chuanbo Hao

“…We characterized the grayscale and texture feature patterns of coal-rock media under varying degrees of interference and established a comprehensive multi-element image training sample library. …”
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Machine Learning-Driven Acoustic Feature Classification and Pronunciation Assessment for Mandarin Learners by Gulnur Arkin, Tangnur Abdukelim, Hankiz Yilahun, Askar Hamdulla

“…Based on acoustic feature analysis, this study systematically examines the differences in vowel pronunciation characteristics among Mandarin learners at various proficiency levels. …”
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A novel Swin transformer based framework for speech recognition for dysarthria by Rabbia Mahum, Ismaila Ganiyu, Lotfi Hidri, Ahmed M. El-Sherbeeny, Haseeb Hassan

“…Firstly, the speech is converted into mel-spectrograms to reflect the maximum patterns of voice signals. Despite the ST’s initial aim to effectively extract the local and global visual features, it still prioritizes global features. …”
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Deep Learning with Dual-Channel Feature Fusion for Epileptic EEG Signal Classification by Bingbing Yu, Mingliang Zuo, Li Sui

“…Background: Electroencephalography (EEG) signals play a crucial role in diagnosing epilepsy by reflecting distinct patterns associated with normal brain activity, ictal (seizure) states, and interictal (between-seizure) periods. …”
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Human brain state dynamics are highly reproducible and associated with neural and behavioral features. by Kangjoo Lee, Jie Lisa Ji, Clara Fonteneau, Lucie Berkovitch, Masih Rahmati, Lining Pan, Grega Repovš, John H Krystal, John D Murray, Alan Anticevic

“…In healthy young adults, we identify reproducible spatiotemporal features of co-activation patterns at the single-subject level. …”
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Reconstructing coastal ponds functional classification: Integration of multi-feature remote sensing by Yijun Tong, Chen Lin, Ke Song, Tingchen Jiang, Ronghua Ma, Wenzhuo Cui, Danhua Ma, Jianchun Chen, Zhenxing Wang, Xiaofen Bai

“…Above all, the PWS classification system and data products developed in this study reveal the diverse relationships among “functional types-remote sensing features-geographical patterns” regarding PWS, implicating a crucial foundation for clarifying the ecological functional value of PWS and appropriate planning in the coastal zone.…”
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Improvement and Optimization of Feature Selection Algorithm in Swarm Intelligence Algorithm Based on Complexity by Bingsheng Chen, Huijie Chen, Mengshan Li

“…Feature selection, as an effective data processing method, has become a hot research topic in the fields of machine learning, pattern recognition, and data mining and has received extensive attention and attention. …”
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Malicious software identification based on deep learning algorithms and API feature extraction by Wei Sun

“…This study contributes to the in-depth exploration of semantic information and behavioral patterns of application programming interface call sequences. …”
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Distributed Photovoltaic Communication Anomaly Detection Based on Spatiotemporal Feature Collaborative Modeling by Li Di, Zhuo Lv, Hao Chang, Junfei Cai

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XGBoost Algorithm for Cervical Cancer Risk Prediction: Multi-dimensional Feature Analysis by Sudi Suryadi, Masrizal

“…This performance profile indicates adept navigation of the delicate balance between missed diagnoses and unnecessary interventions. Feature importance analysis revealed a multifaceted risk landscape, where screening test results contributed substantial predictive power (approximately 60%), complemented by demographic and behavioral factors, including age, reproductive history, and contraceptive usage patterns. …”
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Unsupervised feature selection based on generalized regression model with linear discriminant constraints by Xiangguang Dai, Mingyu Guan, Facheng Dai, Wei Zhang, Tingji Zhang, Hangjun Che, Xiangqin Dai

“…Benefited from this, the relationships and patterns within the high-dimensional data are retained in the reduced-dimensional feature space. …”
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N6-methyladenine identification using deep learning and discriminative feature integration by Salman Khan, Islam Uddin, Sumaiya Noor, Salman A. AlQahtani, Nijad Ahmad

“…In this study, we present Deep-N6mA, a novel Deep Neural Network (DNN) model incorporating optimal hybrid features for precise 6 mA site identification. The proposed framework captures complex patterns from DNA sequences through a comprehensive feature extraction process, leveraging k-mer, Dinucleotide-based Cross Covariance (DCC), Trinucleotide-based Auto Covariance (TAC), Pseudo Single Nucleotide Composition (PseSNC), Pseudo Dinucleotide Composition (PseDNC), and Pseudo Trinucleotide Composition (PseTNC). …”
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Imaging features and prognostic significance of immune checkpoint inhibitor–related pneumonitis in NSCLC by Xueqi Wang, Jingyi Yang, Jiahui E, Fan Liu, Qiliang Wang, Yuwei Zhang, Jing Wang, Ying Liu

“…Fifty-one patients (50.0%) were identified as having organizing pneumonia (OP) pattern, followed by nonspecific interstitial pneumonia (NSIP) pattern in 28 patients (27.4%), hypersensitivity pneumonitis (HP) pattern in 6 patients (5.9%), and diffuse alveolar damage (DAD) pattern in 2 patients (2.0%). …”
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Developmental features of multi-word expressions in spoken discourse by Chinese learners of English by Huiping Zhang, Xingzuo Wang

“…To address this gap, this study aims to investigate the current status and developmental features of MWE use in spoken English by Chinese learners of English across three proficiency levels based on Nattinger and DeCarricos’ classification framework of MWEs. …”
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Exploring the potentialities and challenges of deep learning for simulation and prediction of urban sprawl features by Ange Gabriel Belinga, Stéphane Cedric Tékouabou Koumetio, Mohamed El Haziti

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