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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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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Design of an improved graph-based model for real-time anomaly detection in healthcare using hybrid CNN-LSTM and federated learning by G Muni Nagamani, Chanumolu Kiran Kumar

“…This model improves the anomaly detection to an F1-score of 0.92, which means a performance increase of 15 % over all unimodal approaches. The proposed methods offer multifaceted solutions that provide advanced machine learning techniques, second-by-second real-time processing, and strict privacy measures all at once. …”
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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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Machine learning-based source apportionment and source-oriented probabilistic ecological risk assessment of heavy metals in urban green spaces by Jun Li, Jia-Yi Lu, Xin-Ying Tuo, Chao Wang, Jun-Zhuo Liu, Zhan-Dong Gao, Cun-Hao Yu, Fei Zang

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Multilingual competency and academic performance: a machine learning-based analysis of the 2022/2023 Somaliland national primary exam data by Jibril Abdikadir Ali, Mustafe Khadar Abdi, Tawakal Abdi Ali, Abdisalan Hassan Muse, Mukhtar Abdi Omar, Mukhtaar Axmed Cumar

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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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The Correlation of External Motivation and Agency Position in The Educational Activity of Primary School Students by Tsoy L.V., Kulagina I.Y.

“…Kulagina), the projective method "Attitude to learning" (O.N. Pakhomova) and the projective method of unfinished sentences. …”
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Large Language Models Outperform Traditional Natural Language Processing Methods in Extracting Patient-Reported Outcomes in Inflammatory Bowel Disease by Perseus V. Patel, Conner Davis, Amariel Ralbovsky, Daniel Tinoco, Christopher Y.K. Williams, Shadera Slatter, Behzad Naderalvojoud, Michael J. Rosen, Tina Hernandez-Boussard, Vivek Rudrapatna

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Correlation between computational thinking skills and cognitive learning outcomes: Insights from genetic trait inheritance based on Mendel's laws by Ade Suryanda, Yulilina Retno Dewahrani, Siti Nur Afifah

“…The tests that have been carried out show that there is a significant positive and linear relationship between computational thinking skills and cognitive learning outcomes of genetic trait inheritance based on Mendel’s law. …”
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The influence of perceived social loafing on knowledge sharing intentions among college students by N. T. Duong, T. D. Pham Thi

“…Based on the findings, the authors suggest that teachers should not only enhance students’ learning goal orientation, decrease perceived social loafing to promote the intention to share knowledge in teams, but also make students have positive attitudes towards KS.…”
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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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Performance and hypothetical clinical impact of an mNGS-based machine learning model for antimicrobial susceptibility prediction of five ESKAPEE bacteria by Yaoguang Li, Sizhen Liu, Peng Han, Jun Lei, Huifen Wang, Weiwei Zhu, Zihui Dong, Yize Zhang, Zhi Jiang, Beiwen Zheng, Guanhua Rao, Zujiang Yu, Ang Li

“…The secondary outcomes included the proportion of patients who could benefit from mNGS-based AST. It could allow earlier and suitable antibacterial adjustments in 32.05% of culture-positive patients (25/78) and offer actionable antimicrobial susceptibility results in 16.67% of culture-negative cases (6/36). mNGS-based AST offers a promising approach for individualized antibacterial therapy.IMPORTANCEMetagenomic next-generation sequencing (mNGS)-based antimicrobial susceptibility prediction (AST) is a novel method for predicting the antimicrobial susceptibility of ESKAPEE bacteria using a machine learning approach and short-read sequencing data. …”
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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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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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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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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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