Development of Machine Learning–Based Risk Prediction Models to Predict Rapid Weight Gain in Infants: Analysis of Seven Cohorts by Miaobing Zheng, Yuxin Zhang, Rachel A Laws, Peter Vuillermin, Jodie Dodd, Li Ming Wen, Louise A Baur, Rachael Taylor, Rebecca Byrne, Anne-Louise Ponsonby, Kylie D Hesketh

“…MethodsData from 7 Australian and New Zealand cohorts were pooled for risk model development and validation (n=5233). …”
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Deep learning-based risk stratification of ductal carcinoma in situ using mammography and abbreviated breast magnetic resonance imaging by Tingfeng Zhang, Tingting Cui, Zhenjie Cao, Jintao Hu, Jintao Hu, Jie Ma

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A machine learning model accurately identifies glycogen storage disease Ia patients based on plasma acylcarnitine profiles by Joost Groen, Bas M. de Haan, Ruben J. Overduin, Andrea B. Haijer-Schreuder, Terry GJ Derks, M. Rebecca Heiner-Fokkema

“…As GSD Ia patients demonstrate altered lipid metabolism and mitochondrial fatty acid oxidation, we built a machine learning model to identify GSD Ia patients based on plasma acylcarnitine profiles. …”
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Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines by Qin Li, Nan Lin, Zuheng Wang, Yuexi Chen, Yuli Xie, Xuemei Wang, Jirui Tang, Yuling Xu, Min Xu, Na Lu, Yiqian Huang, Jiamin Luo, Zhenfang Liu, Li Jing

“…This study aimed to analyze pathogen distribution, drug-resistance patterns and develop a novel predictive model for 30-day mortality in HM patients with BSIs. Methods A retrospective analysis of 231 HM patients with positive blood cultures was conducted. …”
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Machine learning-based prediction of carotid intima–media thickness progression: a three-year prospective cohort study by An Zhou, Kui Chen, Kui Chen, Yonghui Wei, Qu Ye, Qu Ye, Yuanming Xiao, Rong Shi, Jiangang Wang, Wei-Dong Li

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Effectiveness of Radiomics-Based Machine Learning Models in Differentiating Pancreatitis and Pancreatic Ductal Adenocarcinoma: Systematic Review and Meta-Analysis by Lechang Zhang, Dewei Li, Tong Su, Tong Xiao, Shulei Zhao

“…Some investigators have explored radiomics-based machine learning (ML) models for distinguishing PDAC from MFP. …”
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Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer by Dong Pan, Dong Pan, Dong Pan, Cheng-Yan Zhang, Cheng-Yan Zhang, Cheng-Yan Zhang, Ya-Fei Wang, Ya-Fei Wang, Shuang Liu, Shuang Liu, Shuang Liu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu

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Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization by Dawen Wu, Yanfei Li, Zeyi Yang, Teng Yin, Xiaohang Chen, Jingyu Liu, Wenyi Shang, Bin Xie, Guoyuan Yang, Haixian Zhang, Longqian Liu

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A condition diagnosis method for subway track structures employing distributed optical fiber sensing by Hong Han, Xiaopei Cai, Liang Gao

“…First, a method for constructing a correlation model for strain monitoring data based on the optimal space window is proposed to realize the division of measuring points to reduce the computational complexity, and then, the deep generative adversarial network model with residual learning is constructed. …”
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PENERAPAN INQUIRY BASED LEARNING UNTUK MENGETAHUI RESPON BELAJAR SISWA PADA MATERI KONSEP DAN PENGELOLAAN KOPERASI by Heru Kusmaryono, Rokhis Setiawati

“…The results showed that students gave<br />positive responses toward the application of Inquiry Based Learning method since<br />students’ responses were very high at 85.51%.…”
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Development and Evaluation of a Virtual Reality-Based Mandarin Language Learning System Enriched with Chinese Cultural and Geographical Contexts by Rizaldi Eko Prasetyo, Esther Irawati Setiawan, Joan Santoso

“…After testing using this method, the results obtained were an increase in learning outcomes of 22% from learning that initially used conventional learning to learning based on Virtual Reality technology. …”
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THE CORRELATION BETWEEN LEARNING STRATEGIES AND STUDENTS’ WRITING ACHIEVEMENT THROUGH PROCESS-BASED APPROACH IN THE THINK-PAIR-SHARE TECHNIQUE by Nirmala Bestari, Agustinus Bambang Setiyadi, Flora Flora

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SED-NET: Real-Time Suspicious Event Detection via Deep Learning-Based Di-Stream Neural Network by D. Siva Senthil, T. S. Sivarani

“…This research introduces a novel deep learning-based SED-NET model for detecting suspicious events in public places. …”
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Development of Educational Game-assisted Accounting Learning Media based on Role-Playing Game to Improve Students' Analytical Abilities by Dian Novianti Sitompul, Faisal Rahman Dongoran, Harningsih Fitri

“…This study aims to develop educational game-assisted accounting learning media based on role playing game to improve students' analytical abilities. …”
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GLOPS: A Hybrid Approach for Enhanced Scheduling in Cloud Computing Environments via Machine Learning-Based Process Prediction by Syed Abu Ammar Muhammad Zarif, Layla Kader Suma, Md. Sadat Rahman, Md. Motaharul Islam, Phuoc Hung Pham, Phong Dung Thi Nguyen, Nguyen Thanh Binh

“…In order to mitigate these challenges, this research proposes a comprehensive strategy that incorporates machine learning based process prediction and metaheuristic optimization techniques in the process scheduling. …”
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Damage Identification of Railway Bridge KW51 Conditions Using Deep-Learning-Based 1D CNN Model by Ali Al-Ghalib, Sawsan Mahmoud

“…The 1D CNN classification algorithm is compared with a statistical-based ML model and another CNN model. The alternative classification model uses human-derived damage-sensitive features extracted from Principal Components Analysis (PCA) in the supervised Linear Discriminant Analysis (LDA) method. …”
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Interculture-Based Language Learning Model to Improve Prospective English Teachers’ Speaking Skills Viewed From Linguistic Awareness by Haerazi, Lalu Ari Irawan, Rimajon Sotlikova

“…This study aimed to know the use of the interculture-based language learning (IBLL) model to improve learners’ speaking skills integrated with linguistic awareness and their responses to learning experiences. …”
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Validity of problem-based learning biodiversity e-book integrating Ruwat Petirtaan Jolotundo's local wisdom for science literacy by Yusnita Ivaningtias, Sifak Indana, Novita Kartika Indah

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DLBWE-Cys: a deep-learning-based tool for identifying cysteine S-carboxyethylation sites using binary-weight encoding by Zhengtao Luo, Zhengtao Luo, Zhengtao Luo, Qingyong Wang, Qingyong Wang, Qingyong Wang, Yingchun Xia, Yingchun Xia, Yingchun Xia, Xiaolei Zhu, Xiaolei Zhu, Xiaolei Zhu, Shuai Yang, Shuai Yang, Shuai Yang, Zhaochun Xu, Zhaochun Xu, Lichuan Gu, Lichuan Gu, Lichuan Gu

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A BERT-based rice enhancer identification model combined with sequence-representation differential entropy interpretation by Yajing Pu, Xintong Hao, Zhaoqi Zheng, Huiyan Ma, Zhibin Lv

“…Enhancers, as key elements regulating the spatiotemporal-specific expression of genes, represent a core challenge in functional genomics due to their precise identification requirements. Current deep learning-based methods for rice enhancer identification face limitations primarily in feature extraction efficiency and the generalization capabilities of model architectures. …”
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