Deep learning-enabled exploration of global spectral features for photosynthetic capacity estimation by Xianzhi Deng, Xiaolong Hu, Liangsheng Shi, Chenye Su, Jinmin Li, Shuai Du, Shenji Li

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POD-Based Machine Learning Approach for Coupled EM-Thermal Analysis in Microwave Heating by Jeong-Wan Lee, Gyu-Sik Choi, Sung-Jun Yang

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Progress and trends on machine learning in proteomics during 1997-2024: a bibliometric analysis by Chao Tan, Hao Liu, Zhen Zhang, Xinyu Liu, Yinquan Ai, Xiumin Wu, Enlin Jian, Yongyan Song, Jin Yang

“…AlphaFold2-related research received the highest citations, reflecting the transformative role of deep learning in protein structure prediction. Thematic clustering revealed key research foci, including deep learning algorithms, protein–protein interaction prediction, and integrative multi-omics analysis. …”
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Leveraging survival analysis and machine learning for accurate prediction of breast cancer recurrence and metastasis by Shahd M. Noman, Youssef M. Fadel, Mayar T. Henedak, Nada A. Attia, Malak Essam, Sarah Elmaasarawii, Fayrouz A. Fouad, Esraa G. Eltasawi, Walid Al-Atabany

“…Key prognostic factors were identified through survival analysis. LightGBM, XGBoost, and Random Forest models were employed and validated against data from the Baheya Foundation. …”
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Aspect-Based Sentiment Analysis Through Graph Convolutional Networks and Joint Task Learning by Hongyu Han, Shengjie Wang, Baojun Qiao, Lanxue Dang, Xiaomei Zou, Hui Xue, Yingqi Wang

“…Aspect-based sentiment analysis (ABSA) through joint task learning aims to simultaneously identify aspect terms and predict their sentiment polarities. …”
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Effective identification of Alzheimer’s disease in mouse models via deep learning and motion analysis by Yuanhao Liang, Zhongqing Sun, Kin Chiu, Yong Hu

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Coastal Students’ Perception of Synchronous and Asynchronous Online Learning: A Rasch Model Analysis by Subroto Gatot

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Machine Learning Approach to Aerodynamic Analysis of NACA0005 Airfoil: ANN and CFD Integration by Taiba Kouser, Dilek Funda Kurtulus, Srikanth Goli, Abdulrahman Aliyu, Imil Hamda Imran, Luai M. Alhems, Azhar M. Memon

“…This study presents a machine learning approach to predict the unsteady aerodynamic performance of a NACA0005 airfoil. …”
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Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease by Hsin-Yueh Liang, Hsin-Yueh Liang, Kai-Cheng Hsu, Kai-Cheng Hsu, Kai-Cheng Hsu, Shang-Yu Chien, Chen-Yu Yeh, Ting-Hsuan Sun, Meng-Hsuan Liu, Kee Koon Ng

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Analysis of Formative and Summative Evaluation Implementation in Physics Learning Process at MA Masyariqul Anwar by Romadon Romadon

“…The research method used is a qualitative method with a case study approach. Data were collected through observation, interviews, and document analysis. …”
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The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma by Binyu Wang, Di Liu, Danfei Shi, Xinmin Li, Yong Li

“…Immunohistochemistry from HPA confirmed consistency between protein levels and RNA-seq data. Furthermore, pan-cancer analysis indicated that these genes are highly expressed across various cancer types. …”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…The dataset includes features such as fundamental frequency (Fo), jitter, shimmer, noise-to-harmonics ratio (NHR), and non-linear dynamic complexity measures. Exploratory data analysis (EDA) was conducted to identify patterns and relationships in the data. …”
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Comparative Analysis of Machine Learning Models for Predicting Contaminant Concentration Distributions in Hospital Wards by Chonggang Zhou, Yunfei Ding

“…In this study, contaminant concentration data from hospital wards were obtained through experimentally validated computational fluid dynamics (CFD) simulations. …”
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Harnessing AI for peer-to-peer learning support: Insights from a bibliometric analysis by Mark Wilson-Trollip

“…The analysis aims to determine whether institutions leverage AI for peer-to-peer learning as part of peer support. …”
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Assessing Data Fusion in Sensory Devices for Enhanced Prostate Cancer Detection Accuracy by Jeniffer Katerine Carrillo Gómez, Carlos Alberto Cuastumal Vásquez, Cristhian Manuel Durán Acevedo, Jesús Brezmes Llecha

“…The signals were subjected to data preprocessing algorithms to prepare them for analysis. …”
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Advanced QSPR modeling of profens using machine learning and molecular descriptors for NSAID analysis by W. Eltayeb Ahmed, Muhammad Farhan Hanif, Muhammad Kamran Siddiqui, Brima Gegbe

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TaxaCal: enhancing species-level profiling accuracy of 16S amplicon data by Qingrong Shen, Xiaoqian Fan, Yangyang Sun, Hao Gao, Xiaoquan Su

“…Abstract Background 16S rRNA amplicon sequencing is a widely used method for microbiome composition analysis due to its cost-effectiveness and lower data requirements compared to metagenomic whole-genome sequencing (WGS). …”
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Analysis of the Ability to Understand Mathematical Concepts Based on Student Learning Styles in Calculus Courses by Nur Qomariyah Nawafilah, Masruroh Masruroh

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Comparative Analysis of Oversampling and SMOTEENN Techniques in Machine Learning Algorithms for Breast Cancer Prediction by Tri Yulian, Erliyan Redy Susanto

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ANALYSIS OF DIFFICULTIES OF MATHEMATICS EDUCATION STUDENTS IN BLENDED LEARNING AFTER COVID-19 PANDEMIC by Suci Dahlya Narpila, Ammamiarihta Ammamiarihta, Siti Aminah Nababan

“…This of course cannot be left alone, it is necessary to in depth analysis of student difficulties when took blended learning and then find the right solution to solve these difficulties. …”
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