Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis by Lu Xing, Tao Wu, Li Yu, Nian Zhou, Zhao Zhang, Yunjing Pu, Jinnan Wu, Hong Shu

“…This study aims to screen potential diagnostic indicators affected by DNA methylation for psoriasis based on bioinformatics using multiple machine learning algorithms and to preliminarily explore its molecular mechanisms. …”
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An Early Detection of Asthma Using BOMLA Detector by Md. Abdul Awal, Md. Shahadat Hossain, Kumar Debjit, Nafiz Ahmed, Rajan Dev Nath, G. M. Monsur Habib, Md. Salauddin Khan, Md. Akhtarul Islam, M. A. Parvez Mahmud

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Development of an upper limb muscle strength rehabilitation assessment system using particle swarm optimisation by Chuangan Zhou, Siqi Wang, Meiyi Wu, Wei Lai, Junyu Yao, Xingyue Gou, Hui Ye, Jun Yi, Dong Cao

“…Simultaneously, triaxial kinematic data of the glenohumeral joint were obtained via an MPU6050 inertial measurement unit, processed through quaternion-based orientation estimation. Machine learning models, including Backpropagation Neural Network (BPNN), Support Vector Machines (SVM), and particle swarm optimization algorithms (PSO-BPNN, PSO-SVR), were applied for regression analysis. …”
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CREATE: cell-type-specific cis-regulatory element identification via discrete embedding by Xuejian Cui, Qijin Yin, Zijing Gao, Zhen Li, Xiaoyang Chen, Hairong Lv, Shengquan Chen, Qiao Liu, Wanwen Zeng, Rui Jiang

“…Here, we present CREATE, a multimodal deep learning framework based on Vector Quantized Variational AutoEncoder, tailored for comprehensive CRE identification and characterization. …”
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Digital Biomarkers for Diagnosis of Muscle Disorders Using Stimulated Muscle Contraction Signal by Kwangsub Song, Sangui Choi, Jin-Hong Shin, Woo-Hyeon Son, Hyuntae Park, Hooman Lee, Nam-Jong Paik

“…Finally, to estimate the strength and endurance of the muscle, the feature vector was passed through the DB estimation model learned through the MLP. …”
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A Novel Skeletonization Algorithm for Topologically Complex Structures: Comparative Analysis and Application to Renal Arterial Trees by Katarzyna Heryan, Stefan-Daniel Caliman

“…Without proper reconstruction, skeletonization, and graph representation, raw <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-CT data remains an unstructured point cloud, unsuitable for quantitative analysis. State-of-the-art methods, including voxel coding, geometric flow, gradient vector flow, and learning-based approaches, fail to meet key performance indicators (KPIs), such as one-voxel-wide centerline extraction, topological preservation, suppression of false bifurcations, and robustness to noise. …”
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Macrophage Infiltration Correlated with IFI16, EGR1 and MX1 Expression in Renal Tubular Epithelial Cells Within Lupus Nephritis-Associated Tubulointerstitial Injury via Bioinformat... by Tian M, Tang M, Chen C, Lin Y, Chen H, Xu Y

“…Based on the machine learning results, we identified IFI16, EGR1 and MX1 were key diagnostic genes for tubulointerstitial injury associated with LN. …”
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MATLAB Application for User-Friendly Design of Fully Convolutional Data Description Models for Defect Detection of Industrial Products and Its Concurrent Visualization by Fusaomi Nagata, Shingo Sakata, Keigo Watanabe, Maki K. Habib, Ahmad Shahrizan Abdul Ghani

“…Models supported by the application include the following original designs: convolutional neural network (CNN), transfer learning-based CNN, NN-based support vector machine (SVM), convolutional autoencoder (CAE), variational autoencoder (VAE), fully convolution network (FCN) (such as U-Net), and YOLO. …”
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Identification and Validation of Key Genes Related to Lipophagy in Osteoporosis by Hu YX, Zuo ML, Wu Y, Yang Y, Shi XB, Zhang Q, Wu J, Xie RQ, Bi Y, Lin B, Mo C

“…Subsequently, multiple bioinformatics tools were used to reveal the associations between key genes and OP. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of key genes.Results: Eight signature genes were identified by machine learning. …”
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Predicting seasonal influenza using supermarket retail records. by Ioanna Miliou, Xinyue Xiong, Salvatore Rinzivillo, Qian Zhang, Giulio Rossetti, Fosca Giannotti, Dino Pedreschi, Alessandro Vespignani

“…We make use of the Support Vector Regression (SVR) model to produce the predictions of seasonal flu incidence. …”
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DATA MINING ALGORITHMS FOR PREDICTION OF STUDENT TEACHERS’ PERFORMANCE IN ICT: A SYSTEMATIC LITERATURE REVIEW by Juma Habibu Shindo, Mohamedi Mohamedi Mjahidi, Mohamed Dewa Waziri

“… Poor ICT performance in teacher training colleges makes it more difficult for the majority of teachers to successfully use ICT resources in their teaching and learning. When teachers can efficiently utilize ICT resources, it empowers them to update their knowledge through online learning, consequently enhancing the overall quality of teaching and learning. …”
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LncRNAs regulates cell death in osteosarcoma by Ping’an Zou, Zhiwei Tao, Zhengxu Yang, Tao Xiong, Zhi Deng, Qincan Chen, Li Niu

“…Univariate Cox regression analysis was employed to identify lncRNAs associated with osteosarcoma treatment. Three machine learning algorithms—Support Vector Machine, Random Forest, and Generalized Linear Model—were utilized to select feature genes. …”
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Illumination-adaptative granularity progressive multimodal image fusion method by Chuanyun WANG, Dongdong SUN, Mingqi ZHOU, Tian WANG, Qian GAO, Zhaokui LI

“…This module leverages a pretrained image encoder to model the scene, generating scene vectors that are processed through various linear layers. …”
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Differences in emotional expression among college students: a study on integrating psychometric methods and algorithm optimization by Xiaozhu Chen

“…In order to improve the precision of data analysis, random forests, support vector machines, and neural network machine learning algorithms were applied, and the variance analysis was used to calculate and compare the emotional differences of different genders and academic backgrounds in different grades. …”
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Classification of power grip and precision grip in children using an EIT-based tactile sensor by Ryunosuke Asahi, Shumpei Toriyama, Yasuyo Minagawa, Shunsuke Yoshimoto, Hiroki Sato

“…The classification features were voltage vectors and reconstructed images obtained from the sensor, and two machine learning methods were used as the classifiers. …”
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Listening to the verses: unveiling phonetic contrasts in Li Bai and Du Fu’s poetry by Yingying Meng, Yuwei Wan, Chunyu Kit

“…This study applies sound symbolism principles to explore the emotional and perceptual effects of sounds in their poetry, focusing on a quantitative phonetic comparison of their works. Utilising character sound information extracted from the rhyme book Guangyun (廣韻 extended rhymes), their poems were transformed into sound vectors for authorship attribution by machine learning models. …”
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Wildlife law and policy by S. Bertouille

“…A sociologic approach is required to take into account those human groups whose interests are divergent, facilitating communication and collaborative learning among these users of the same ecosytem. Obstacles should be addressed and solutions devised to protect and encourage a sustainable use of this ecosystem in, as much as possible, a win–win relationship. …”
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Pansharpening via Multiscale Embedding and Dual Attention Transformers by Wensheng Fan, Fan Liu, Jingzhi Li

“…However, long-range and local dependencies modeling and multiscale feature learning are all essential to the pansharpening task. …”
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MMAR-Net: A Multi-Stride and Multi-Resolution Affine Registration Network for CT Images by Fu Zhou, Fei Luo, Ruoshan Kong, Yi-Ping Phoebe Chen, Feng Liu

“…Furthermore, we make use of the image features at multiple scales by dot product between two feature vectors, which could enhance the robustness of image representation. …”
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