Stroke Prediction Using Deep Learning and Transfer Learning Approaches by Dong-Her Shih, Yi-Huei Wu, Ting-Wei Wu, Huei-Ying Chu, Ming-Hung Shih

“…According to the experimental results, this study effectively reduced the false negative rate (FNR) and false positive rate (FPR) of stroke prediction and improved the overall accuracy of stroke prediction through the category imbalance treatment and deep learning method.…”
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Enhanced security for medical images using a new 5D hyper chaotic map and deep learning based segmentation by S. Subathra, V. Thanikaiselvan

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Machine Learning-Based Prediction Model for Predicting the Effect of the Serum γKlotho Level on Susceptibility to Coronary Heart Disease by Guo ZT, Yu XL, Cheng H, Naman T

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Role of necroptosis and immune infiltration in essential thrombocytosis by Guangming Li, Ying Guo, Yuanyuan Zhang

“…GSE57793 and GSE26049 datasets were recruited to identify necroptosis differentially expressed genes based on differential gene identification, necroptosis gene sets and data machine learning. …”
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Industrial-Grade 3D Detection for Laser Cleaning of Metallic Components Based on Neural Radiance Fields and Temporal-Spatial Learning by Dandan Qi

“…This paper proposes an industrial-grade 3D detection algorithm based on Neural Radiance Field (NeRF) and spatiotemporal consistency learning. …”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…The low recurrence risk group based on IRGS exhibited a stronger immune phenotype and better survival prognosis, which may be associated with higher infiltration of CD4 + and CD8 + T cells. …”
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DeepMiRBP: a hybrid model for predicting microRNA-protein interactions based on transfer learning and cosine similarity by Sasan Azizian, Juan Cui

“…Advanced bioinformatics tools are urgently needed to facilitate this research. Methods We present DeepMiRBP, a novel hybrid deep learning model specifically designed to predict microRNA-binding proteins by modeling molecular interactions. …”
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Identification and validation of endoplasmic reticulum stress-related diagnostic biomarkers for type 1 diabetic cardiomyopathy based on bioinformatics and machine learning by Qiao Tang, Yanwei Ji, Zhongyuan Xia, Yuxi Zhang, Chong Dong, Chong Dong, Qian Sun, Shaoqing Lei

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Convolutional transform learning based fusion framework for scale invariant long term target detection and tracking in unmanned aerial vehicles by Fatma S. Alrayes, Nazir Ahmad, Asma Alshuhail, Menwa Alshammeri, Ali Alqazzaz, Hassan Alkhiri, Jehad Saad Alqurni, Yahia Said

“…The model increases targeted accuracy and decreases false positives using real-time data and machine learning (ML) methods. …”
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An AI recognition method for children's clinical operative pain by skin potential (SP) signal by Mingxuan Huang, Cangcang Fu, Linbo Chui, Jiadong He, Xiaozhi Wang, Jikui Luo, Bin Wu, Yonggang Chen, Shaohua Hu, Jihua Zhu, Yubo Li

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Extensive comparison of protein sequence-based bioinformatics applications for predicting lysine succinylation sites: a comparative review by Hussam Alsharif

“…Succinylation site identification is an area of high research interest, and sequence-based prediction methods using machine learning and deep learning have been developed based on experimentally confirmed data of succinylation sites, aiming to be highly accurate, robust, quick, and cost-efficient. …”
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Sound Quality Prediction Method of Dual-Phase Hy-Vo Chain Transmission System Based on MFCC-CNN and Fuzzy Generation by Jiabao LI, Lichi AN, Yabing CHENG, Haoxiang WANG

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Automatic detecting multiple bone metastases in breast cancer using deep learning based on low-resolution bone scan images by Jialin Shi, Ruolin Zhang, Zongyao Yang, Zhixian Chen, Zhixin Hao, Li Huo, Ji Wu, Qiang Sun, Yali Xu

“…WBS images with breast cancer bone metastasis have the characteristics of low resolution, small foreground, and multiple lesions, hindering the widespread application of deep learning-based models. Automatically detecting a large number of densely small lesions on low-resolution WBS images remains a challenge. …”
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Deep Learning-Based Surface Temperature Prediction for a Porous Radiant Burner Using Thermocouple-Calibrated Thermal Infrared Images by Hao-Yu Hsieh, Shenqyang Shy, Wei-Wun Wang, Yung-Chien Chou

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A tumor-infiltrating B lymphocytes -related index based on machine-learning predicts prognosis and immunotherapy response in lung adenocarcinoma by Jiale Fang, Siyuan Yu, Wei Wang, Wei Wang, Cheng Liu, Xiaojia Lv, Jiaqi Jin, Xiaomin Han, Xiaomin Han, Xiaomin Han, Fang Zhou, Yukun Wang

“…A comprehensive machine learning approach, utilizing ten distinct algorithms, facilitated the creation of a TILB-related index (BRI) across the TCGA, GSE31210, and GSE72094 datasets. …”
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Network intrusion detection based on improved KNN algorithm by Hongsheng Bao, Jie Gao

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運用問題導向學習法提升國中學生學習成效之研究 －以人文通論地理結合校本課程為例 Enhance Learning Efficiency in Junior High Schools through Problem-based Learning: The Example of Human Geography in a School-based Curricu... by 葉宜宣 Yi-Hsuan Yeh

“…Problem-based Learning (PBL) is student-centered; students discuss true events, while teachers guide them and provide mini-lectures. …”
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Exploration for the physical origin and impact of chemical short-range order in high-entropy alloys: Machine learning-assisted study by Panhua Shi, Zhen Xie, Jiaxuan Si, Jianqiao Yu, Xiaoyong Wu, Yaojun Li, Qiu Xu, Yuexia Wang

“…In this study, we introduced a set of interpretable ML workflows and determined the best algorithm (kernel ridge regression (KRR)) for predicting the atomic stress in HEAs, which can deepen the understanding of the formation mechanism of CSRO. Based on first-principles calculations and Monte Carlo methods, we obtained information on each atom at the atomic and electronic levels to establish the ML features. …”
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Evaluation of Simulation-based Training in Airway Management among Maiden Workshop Participants in Enugu, Nigeria: A Mixed-method Study by Nwosu ADG, Ossai EN, Amucheazi AO, Onyekwulu FA, Achi J, Ilo DI

“…Conclusion: The training positively impacted on the trainees’ learning and behaviour. …”
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The Bayesian mixture expert recognition model for tobacco leaf curing stages based on feature fusion by Panzhen Zhao, Shijiang Duan, Songfeng Wang, Aihua Wang, Lingfeng Meng, Zhicheng Wang, Yingpeng Dai

“…To address this issue, this study proposes a Bayesian Mixture Expert Recognition Model for Tobacco Leaf Curing Stages based on feature fusion. First, deep learning models (ResNet34, MobileNetV2, EfficientNetb0) are utilized to extract deep features and traditional features positively correlated with curing stages from a constructed tobacco leaf image dataset. …”
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