Integrated cytomembrane proteomics identifies EpCAM/MGST1 as therapeutic targets in metastatic laryngeal carcinoma by Suling Zhuang, Xiaobo Wu, Xiaobo Wu, Xiaobo Wu, Xiaohuang Lin, Zhihan Li, Di Gan, Shixin Wang, Xue Lin, Gongbiao Lin, Gongbiao Lin, Gongbiao Lin, Miao Gao, Miao Gao, Miao Gao

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Promoting Health Literacy With Human-in-the-Loop Video Understandability Classification of YouTube Videos: Development and Evaluation Study by Xiao Liu, Anjana Susarla, Rema Padman

“…Our method optimally combines expert input with algorithmic support, enhancing engagement and aiding medical experts in recommending educational content. …”
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Multiscale Sample Entropy-Based Feature Extraction with Gaussian Mixture Model for Detection and Classification of Blue Whale Vocalization by Oluwaseyi Paul Babalola, Olayinka Olaolu Ogundile, Vipin Balyan

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Simulation-Based Optimization for the Operation of Toll Plaza at Car Park Exit with Mixed Types of Tollbooths and Waiting-Time-Dependent Service by Shanchuan Yu, Yuchuan Du, Jindong Wang, Yishun Li, Yong Zhu

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Comparative Analysis of Computed Tomography and Laparoscopy Data in Preoperative Staging of Gastric Cancer by N. K. Silanteva, T. A. Аgababyan, A. A. Kholeva, V. Yu. Skoropad, Z. N. Shavladze, S. A. Ivanov, L. P. Zhavoronkov

“…The combined use of CT and DL is a current algorithm for examining patients with gastric cancer. …”
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Harnessing the machine learning and nomogram models: elevating prognostication in nonmetastatic gastric cancer with “double invasion” for personalized patient care by Zhenwen Hao, Zhiming Wang, Jinfeng Ma, Yifan Li, Wenbin Zhang

“…Abstract Objective To develop and validate a machine learning framework combined with a nomogram for predicting recurrence after radical gastrectomy in patients with vascular and neural invasion. …”
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Programmable friction control in 3D printed patterned multi-materials: a flexible design strategy by Xinle Yao, Yuxiong Guo, Mingyang Wang, Yaozhong Lu, Zhibin Lu, Xin Jia, Yu Gao, Xiaolong Wang

“…Accurate prediction and control of friction are vital for conserving energy, driving demand for intelligent tribological systems with adaptive control. …”
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Stroke in children and adolescents: topical problems of pre-hospital diagnostics by Y. A. Khachaturov, I. O. Shchederkina, N. F. Plavunov, A. M. Sidorov, E. E. Petryaykina, I. P. Vytkovskaya, V. A. Kadyshev

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How math shapes the world of life science animation by Rafael Oliveira, Evellyn Araujo Dias, Evellyn Araujo Dias, Ricardo Santos, Ricardo Santos, Vinicius Cotta-De-Almeida, José Aguiar Coelho Nt, José Aguiar Coelho Nt, José Aguiar Coelho Nt, Luiz Anastácio Alves

“…With the advances in technology, it is noticeable the educational potential of animation in the field of cell biology, physiology and other basic life science disciplines, revolutionizing the learning process in science. …”
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Sampling calorimeter to measure the photon’s incident angle by Lim GeiYoub, Abe Ryota, Ahn JungKeun, Ji Su-Jeong, Kim Chong, Kim Eun-Joo, Kim Junlee, Kim YoungJun, Kim YoungJun, Kotera Katsushige, Lim Sanghoon, Naito Taichi, Park JeongWoo, Shiomi Koji, Tajima Yasuhisa, Yang Seongbae, Yoshida Hiroshi

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Data Analysis for Emotion Classification Based on Bio-Information in Self-Driving Vehicles by Tae-Yeun Kim, Hoon Ko, Sung-Hwan Kim

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Peculiarities of early diagnosis and tactics of treatment in an acute pancreatitis in pregnant women by Ya. P. Feleshtynskyi, О. V. Golyanovskyi, Т. P. Pavliv

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ADAPTIVE VISION AI by V. Vodyanitskyi, V. Yuskovych-Zhukovska

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Thermal radiation and diffusion effects on MHD sisko fluid flow over a nonlinearly stretchable porous sheet by V. Adilakshmi, Ali Akgül, G. Venkata Ramana Reddy, Murad Khan Hassani

“…For example, elevating the Sisko parameter from 1.0 to 2.0 propels the velocity profile upward by approximately 20%, while the temperature and concentration profiles witness reductions of 10% and 8%, respectively. Moreover, escalating values of the power-law exponent and the nonlinear stretching coefficient contribute to a decline in velocity, temperature, and concentration. …”
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Simultaneous and Proportional Myoelectric Control of Multiple Degrees of Freedom in Individuals With Chronic Hemiparesis by Caleb J. Thomson, W. Caden Hamrick, Jakob W. Travis, Michael D. Adkins, Patrick P. Maitre, Steven R. Edgely, Jacob A. George

“…We collected data from seven hemiparetic patients and systematically explored the root mean squared error (RMSE) of kinematic predictions for various degrees of freedom. We show that proportional position control is possible for multiple hand and wrist motions and that unidirectional DOFs perform better than bidirectional DOFs. …”
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Design and refinement of a clinical trial staffing model within the evolving landscape of oncology clinical trials by Ellen Siglinsky, Hannah Phan, Silviya Meletath, Amber Neal, David E. Gerber, Asal Rahimi, Erin L. Williams

“…Methods: To address individual protocol acuity, the model's algorithms include metrics to account for visit frequency, and the quantity, and types of research-related procedures. …”
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Identification of testicular cancer with T2-weighted MRI-based radiomics and automatic machine learning by Liang Wang, PeiPei Zhang, Yanhui Feng, Wenzhi Lv, Xiangde Min, Zhiyong Liu, Jin Li, Zhaoyan Feng

“…We developed an AutoML method based on the tree-based pipeline optimization tool (TPOT) algorithm to construct a discriminant model. The best pipeline was determined through 100 repeated operations using a 5-fold cross-validation algorithm in TPOT. …”
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Analysis of Beam-Column Designs by Varying Axial Load with Internal Forces and Bending Rigidity Using a New Soft Computing Technique by Wen Huang, Tianhua Jiang, Xiucheng Zhang, Naveed Ahmad Khan, Muhammad Sulaiman

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Characterization of immune microenvironment associated with medulloblastoma metastasis based on explainable machine learning by Fengmao Zhao, Xiangjun Liu, Jingang Gui, Hailang Sun, Nan Zhang, Yun Peng, Ming Ge, Wei Wang

“…Methods ML models were constructed and validated to predict prognosis and metastasis in MB patients. Eight algorithms were evaluated, and the optimal model was selected. …”
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FFTL-Net: a network for the classification of skin diseases based on feature fusion and transfer learning by Xiaowei Song, Yurong Mei, Zhilei Zhao, Hao Chang, Lina Han, Hui Wang, Xinyi Zhang, Guoqiang Wang

“…This represents an improvement of 1.25% and 0.33% compared to the second-ranked algorithm, respectively. The experimental results demonstrate the efficacy of the model in addressing the data imbalance issue in skin disease datasets, with prediction accuracies of at least 93% being achieved for BCC and other rare samples. …”
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