Glaucoma detection in myopic eyes using deep learning autoencoder-based regions of interest by Christopher Bowd, Akram Belghith, Mark Christopher, Makoto Araie, Aiko Iwase, Goji Tomita, Kyoko Ohno-Matsui, Hitomi Saito, Hiroshi Murata, Tsutomu Kikawa, Kazuhisa Sugiyama, Tomomi Higashide, Atsuya Miki, Atsuya Miki, Toru Nakazawa, Makoto Aihara, Tae-Woo Kim, Christopher Kai Shun Leung, Robert N. Weinreb, Linda M. Zangwill

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Machine learning Nomogram for Predicting endometrial lesions after tamoxifen therapy in breast Cancer patients by Cao Shaoshan, Chen Niannian, Ma Ying

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The Impact of Farmland Transfer on Urban–Rural Integration: Causal Inference Based on Double Machine Learning by Yuchen Lu, Jiakun Zhuang, Jun Chen, Chenlu Yang, Mei Kong

“…The analysis of the impact of the 2010 liberalisation of the land transfer policy employs a dual machine learning model, utilising provincial-level data from China spanning 2005 to 2022, to address the limitations of traditional causal inference models while ensuring estimation accuracy. …”
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Research on short-term power load forecasting based on deep reinforcement learning with multiple intelligences by Tianyun Luo, Dunlin Zhu, Jinming Liu, Sheng Yang, Jinglong He, Yuan Fu

“…In this paper, we analyze the multi-intelligence application architecture in power load forecasting, and analyze the function of each intelligent unit applied to short-term power load forecasting; based on clarifying the interaction relationship of each intelligent unit in short-term power load forecasting, we model short-term power load forecasting as a distributed and partially observable Markov decision-making process, which is suitable for multi-intelligence deep reinforcement learning; based on the MATD3 algorithm, a centralized training-distributed execution framework is used to train multiple intelligences within the model to achieve short-term power load forecasting. …”
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Enconv1d Model Based on Pseudolite System for Long-Tunnel Positioning by Changgeng Li, Yuting Zhang, Changshui Liu

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Machine learning-driven prediction model for cuproptosis-related genes in spinal cord injury: construction and experimental validation by Yimin Zhou, Xin Li, Zixiu Wang, Liqi Ng, Rong He, Chaozong Liu, Gang Liu, Xiao Fan, Xiaohong Mu, Yu Zhou, Yu Zhou

“…Three machine learning models (RF, LASSO, and SVM) were constructed to screen candidate genes, and a Nomogram model was used for verification. …”
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Space-scale exploration of the poor reliability of deep learning models: the case of the remote sensing of rooftop photovoltaic systems by Gabriel Kasmi, Laurent Dubus, Yves-Marie Saint-Drenan, Philippe Blanc

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Machine learning prediction and explanation of high intraoperative blood pressure variability for noncardiac surgery using preoperative factors by Zheng Zhang, Yi Duan, Zuozhi Li, Zhifeng Gao, Huan Zhang

“…Abstract Background The objective of this study is to construct an explainable machine learning predictive model for high intraoperative blood pressure variability(IBPV) based on preoperative characteristics, to enhance intraoperative circulatory management and surgical outcomes. …”
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Research on Integrated Control Strategy for Highway Merging Bottlenecks Based on Collaborative Multi-Agent Reinforcement Learning by Juan Du, Anshuang Yu, Hao Zhou, Qianli Jiang, Xueying Bai

“…An integrated control system based on the Factored Multi-Agent Centralized Policy Gradients (FACMAC) algorithm is developed. …”
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Whether case-based teaching combined with the flipped classroom is more valuable than traditional lecture-based teaching methods in clinical medical education: a systematic review... by Xu-Ying Shi, Bing-Rui Lu, Qing Yin, Qiu-Wen Wang, Yong-Qi Fang, Zhi-Gang Sun

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Construction of gas content model based on KPCA-SVR for Southern Sichuan shale gas by Zhong-yuan Liu, Di-Quan Li, Jing Jia, Yun-Qi Zhu, Zhong-Le Wang, Xue-Song Xie

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Image-based machine learning and cluster analysis for urban road network: employing Orange for codeless visual programming by Zuo Zhang, Mengwei Zhang, Xiangxiang Song, Zhi Li

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Dynamic Monitoring of Ecological Environmental Quality in Arid and Semi-Arid Regions: Disparities Among Central Asian Countries and Analysis of Key Driving Factors by Yue Liu, Jinjie Wang, Jianli Ding, Zipeng Zhang, Zhihong Liu, Zihan Zhang, Jinming Zhang, Liya Shi

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Prediction of Distant Metastasis of Renal Cell Carcinoma Based on Interpretable Machine Learning: A Multicenter Retrospective Study by Dong J, Duan M, Liu X, Li H, Zhang Y, Zhang T, Fu C, Yu J, Hu W, Peng S

“…We aimed to establish an interpretable machine learning model for predicting distant metastasis in RCC patients.Methods: We involved a population-based cohort of 121433 patients (mean age = 63 years; 63.58% men) diagnosed with RCC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. …”
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Machine learning for classification of pediatric bipolar disorder with and without psychotic symptoms based on thalamic subregional structural volume by Weijia Gao, Kejing Zhang, Qing Jiao, Linyan Su, Dong Cui, Shaojia Lu, Rongwang Yang

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How can communities better prepare for future disasters? Learning from the tourism community resilience model from Bali, Indonesia by I Putu Gede Eka Praptika, Mohamad Yusuf, Jasper Hessel Heslinga

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Enhancing python learning with PyTutor: Efficacy of a ChatGPT-Based intelligent tutoring system in programming education by Albert C.M. Yang, Ji-Yang Lin, Cheng-Yan Lin, Hiroaki Ogata

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Improving WRF-Chem PM2.5 predictions by combining data assimilation and deep-learning-based bias correction by Xingxing Ma, Hongnian Liu, Zhen Peng

“…Four parallel experiments were conducted during winter 2019: a control experiment directly forecasted by WRF-Chem (experiment name: WRF-Chem); an experiment that assimilated in situ observations based on the GSI (Gridpoint Statistical Interpolation) system (WRF-Chem_DA); an experiment with deep-learning-based BC (WRF-Chem_BC); and an experiment considering the combination of DA on the initial conditions and BC (WRF-Chem_DA_BC). …”
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Designing an educational model based on identity development with an Iranian-Islamic approach for primary school students. by Ali Oladhamzehzadeh, masoumeh oladiyan, Mahmoud Safari

“…The dimensions of the educational model based on the identity development of students with the Iranian-Islamic approach include educational goals and content, teaching and learning methods, instructors and teachers, cultural factors, social factors, psychological factors, media, educational factors, and family factors. …”
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Testing the Applicability and Transferability of Data-Driven Geospatial Models for Predicting Soil Erosion in Vineyards by Tünde Takáts, László Pásztor, Mátyás Árvai, Gáspár Albert, János Mészáros

“…Soil loss was formerly modeled by USLE, thus providing non-observation-based reference datasets for the calibration of parcel-specific prediction models using various ML methods (Random Forest, eXtreme Gradient Boosting, Regularized Support Vector Machine with Linear Kernel), which is a well-established approach in digital soil mapping (DSM). …”
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