Is Implicit Motor Learning Preserved after Stroke? A Systematic Review with Meta-Analysis. by E Kal, M Winters, J van der Kamp, H Houdijk, E Groet, C van Bennekom, E Scherder

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Increased Temporal Variability of Gait in ASD: A Motion Capture and Machine Learning Analysis by Katharine Goldthorp, Benn Henderson, Pratheepan Yogarajah, Bryan Gardiner, Thomas Martin McGinnity, Brad Nicholas, Dawn C. Wimpory

“…The primary data were collected using a VICON^® 3D motion analysis system. …”
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Machine learning classification and driver analysis of diel variability in dissolved oxygen in Taihu Lake by Tingting Luo, Yehui Zhang

“…This study analyzed high-frequency DO data from Sanshandao Island in Taihu Lake (2020–2022) to classify diel DO variation patterns and identify key drivers. …”
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Hybrid Time Series Methods and Machine Learning for Seismic Analysis and Volcano Eruption Predict by Fridy Mandita, Ahmad Ashari, Moh. Edi Wibowo, Wiwit Suryanto

“…Furthermore, the findings offer substantial improvements in the forecasting and risk mitigation associated with volcanic eruptions, hence, advancing reliable seismic analysis methodologies. Ultimately, the method enhances hybrid methods and machine learning for seismic event analysis and volcano monitoring.   …”
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Application of machine learning in intelligent transport systems: a comprehensive review and bibliometric analysis by Mahbub Hassan, Abdullah Al Nafees, Saikat Sarkar Shraban, Arpita Paul, Hridoy Deb Mahin

“…Abstract The integration of machine learning (ML) into intelligent transport systems (ITS) has significantly enhanced the efficiency, security, and sustainability of urban transportation. …”
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Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for thyroid cancer by Peng Zhang, Meizhong Qin, Fen Li, Kunpeng Hu, He Huang, Cuicui Li

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Comparative Analysis of Facial Expression Recognition Methods by Denys - Florin COT

“… This paper aimed to investigate human emotion recognition through the analysis of facial expressions, using both classical machine learning methods and advanced techniques based on deep neural networks. …”
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Analyzing Patient Experience on Weibo: Machine Learning Approach to Topic Modeling and Sentiment Analysis by Xiao Chen, Zhiyun Shen, Tingyu Guan, Yuchen Tao, Yichen Kang, Yuxia Zhang

“…To increase the utility of these data, a machine learning algorithm can be used for topic modeling. …”
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An evolution of forensic linguistics: From manual analysis to machine learning – A narrative review by R. Thamizh Mani, Vikram Palimar, Mamatha Shivananda Pai, T.S. Shwetha, M. Nirmal Krishnan

“…Forensic linguistics has evolved from manual textual analysis to machine learning (ML)-driven methodologies, fundamentally transforming its role in criminal investigations. …”
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Analysis of Demographic, Familial, and Social Determinants of Smoking Behavior Using Machine Learning Methods by Joanna Chwał, Małgorzata Kostka, Paweł Stanisław Kostka, Radosław Dzik, Anna Filipowska, Rafał Jan Doniec

“…This study examines the relationship between smoking habits and family dynamics through a cross-sectional survey of 100 participants, using an anonymous questionnaire to collect demographic data, smoking patterns, and familial interactions. …”
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A Data-Driven Model for the Energy and Economic Assessment of Building Renovations by Giuseppe Piras, Francesco Muzi, Zahra Ziran

“…However, defining effective and economically sustainable interventions remains a challenge, partly due to the variability of building characteristics and the lack of digital tools to support data-driven decision making. This research aims to identify the main factors influencing the energy consumption of buildings by analyzing a large database of building characteristics using machine learning algorithms. …”
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Machine learning analysis of ARVC informed by sodium channel protein-based interactome networks by Yanan Zhu, Hui Zhang, Xuan Zhao, Xin Wang, Lina Xing, Sijie Yao, Xiao Jin, Tingting Li, Ting Dai, Xinyue Ding, Zhen Qi, Zongjun Liu

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A predictive nomogram of thyroid nodules based on deep learning ultrasound image analysis by Yuan Li, Ting Li, Kai He, Xiao-xiao Cui, Lu-lu Zhang, Xiu-liang Wei, Zhi Liu, Mei Wu

“…The binary logistic analysis of the training set revealed that age, echogenic foci, and deep learning predicted values were statistically significant (P<0.05). …”
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Deep Learning in Glaucoma Detection and Progression Prediction: A Systematic Review and Meta-Analysis by Xiao Chun Ling, Henry Shen-Lih Chen, Po-Han Yeh, Yu-Chun Cheng, Chu-Yen Huang, Su-Chin Shen, Yung-Sung Lee

“…<b>Purpose:</b> To evaluate the performance of deep learning (DL) in diagnosing glaucoma and predicting its progression using fundus photography and retinal optical coherence tomography (OCT) images. …”
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Estimation of physico-chemical properties of soil using machine learning by Patience Chizoba Mba, Opegbemi Matthias Busoye, John Temitope Ajayi, Judith Nkechinyere Njoku, Cosmas Ifeanyi Nwakanma, Senorpe Asem-Hiablie, Rammohan Mallipeddi, Tusan Park, Daniel Dooyum Uyeh

“…The study integrated Machine Learning (ML) and Deep Learning (DL) techniques with soil image analysis, employing image feature extraction through Gray-Level Co-occurrence Matrix (GLCM) and Gabor filters to enhance the feature space across 1,388 samples (each consisting of 600 g of soil) and 16 properties. …”
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Identifying shared hub genes in LIRI and MASLD through bioinformatics analysis and machine learning by Yongzhi Zhou, Bing Yin, Yang Yang, Zhongyu Li, Zhanzhi Meng, Shounan Lu, Baolin Qian, Xinglong Li, Yongliang Hua, Hongjun Yu, Yao Fu, Yong Ma

“…Further analysis involved Gene Ontology, KEGG, and machine learning to pinpoint common hub genes and pathways. …”
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Multi-source data joint processing framework for DEM calibration and fusion by Cuilin Yu, Qingsong Wang, Zibo Zhang, Zixuan Zhong, Yusheng Ding, Tao Lai, Haifeng Huang, Peng Shen

“…High-accuracy digital elevation models (DEMs) are essential for remote sensing and geospatial analysis, yet integrating multi-source data over large and complex terrains remains challenging. …”
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Deep learning for human locomotion analysis in lower-limb exoskeletons: a comparative study by Omar Coser, Omar Coser, Christian Tamantini, Christian Tamantini, Matteo Tortora, Matteo Tortora, Leonardo Furia, Rosa Sicilia, Loredana Zollo, Paolo Soda, Paolo Soda

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Establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features by You Wu, Ke Tang, Chunzheng Wang, Hao Song, Fanfan Zhou, Ying Guo

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Evaluation of the ABC pathway in patients with atrial fibrillation: A machine learning cluster analysis by Jingyang Wang, Haiyang Bian, Jiangshan Tan, Jun Zhu, Lulu Wang, Wei Xu, Lei Wei, Xuegong Zhang, Yanmin Yang

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