Construction of a Prediction Model for Energy Consumption in Urban Rail Transit Operations Using a Bottom–Up Approach by Boyu Chen, Ye Lin

“…The factors were grouped based on the scale of the urban rail transit network, and planned indicators were screened using stepwise regression and machine learning eigenvalue methods. Predictive models were then constructed using these planned indicators through multiple linear regression and random forest regression. …”
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FLEM-XAI: Federated learning based real time ensemble model with explainable AI framework for an efficient diagnosis of lung diseases by Sivan Durga, Esther Daniel, Surleese Seetha, Vijaya Kumar Reshma, Vasily Sachnev

“…The computer-aided diagnosis helps medical professionals detect and classify lung diseases from chest X-rays by leveraging medical image processing and central server-based machine learning models. These technologies provide real-time assistance to analyze the input and help efficiently detect the abnormalities at the earliest. …”
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A performance evaluation of silver nanorods PDMS flexible dry electrodes for electrocardiogram monitoring by C. M. Vidhya, Ghanshyam Kumar, Yogita Maithani, Bhanu Duggal, J. P. Singh

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Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework by Abbas Ali Hussein, Morteza Valizadeh, Mehdi Chehel Amirani, Sedighe Mirbolouk

“…In a subsequent step, Machine Learning (ML) algorithms are employed to classify these tumors as malign or benign cases. …”
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Challenges of the Biopharmaceutical Industry in the Application of Prescriptive Maintenance in the Industry 4.0 Context: A Comprehensive Literature Review by Johnderson Nogueira de Carvalho, Felipe Rodrigues da Silva, Erick Giovani Sperandio Nascimento

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Less Is More: The Influence of Pruning on the Explainability of CNNs by Florian Merkle, David Weber, Pascal Schottle, Stephan Schlogl, Martin Nocker

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Prosumer Cost Efficiency and Ensuring Grid Stability Through a Hierarchical PPO Framework in Decentralized Community Energy Management by Ajay Singh, Bijaya Ketan Panigrahi

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Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis by Zohreh Javanmard, Saba Zarean Shahraki, Kosar Safari, Abbas Omidi, Sadaf Raoufi, Mahsa Rajabi, Mohammad Esmaeil Akbari, Mehrad Aria

“…Artificial Intelligence (AI) and Machine Learning (ML) algorithms offer promising solutions for automated survival prediction, driving this study’s systematic review and meta-analysis.MethodsThree online databases (Web of Science, PubMed, and Scopus) were comprehensively searched (January 2016-August 2023) using key terms (“Breast Cancer”, “Survival Prediction”, and “Machine Learning”) and their synonyms. …”
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FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging by Abhilasha Dave, Cong Wang, James Russell, Ryan Herbst, Jana Thayer

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Hyperspectral Detection of Pesticide Residues in Black Vegetable Based on Multi-Classifier Entropy Weight Method by Rongchang Jiang, Guoqiang Zhuang, Shijie Xie, Yang Wang, Guoqi Zhang, Dandan Qu, Wanzhi Wen

“…Models were built using eXtreme gradient boosting, random forest, and support vector machine algorithms. …”
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AI-Driven Comprehensive SERS-LFIA System: Improving Virus Automated Diagnostics Through SERS Image Recognition and Deep Learning by Shuai Zhao, Meimei Xu, Chenglong Lin, Weida Zhang, Dan Li, Yusi Peng, Masaki Tanemura, Yong Yang

“…On this basis, a negative–positive discrimination method combining SERS scanning imaging with a deep learning model (ResNet-18) was developed to analyze probe distribution patterns near the T line. …”
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Advanced AI techniques for classifying Alzheimer’s disease and mild cognitive impairment by Sophie Tascedda, Sophie Tascedda, Sophie Tascedda, Pierfrancesco Sarti, Pierfrancesco Sarti, Veronica Rivi, Claudia Savia Guerrera, Giuseppe Alessio Platania, Mario Santagati, Filippo Caraci, Filippo Caraci, Johanna M. C. Blom, Johanna M. C. Blom

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Advancing Spike Sorting Through Gradient‐Based Preprocessing and Nonlinear Reduction With Agglomerative Clustering by Mohammad Amin Lotfi, Fatemeh Zareayan Jahromy, Mohammad Reza Daliri

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Arsenic toxicity exacerbates China’s groundwater and health crisis by Xin Liu, Fu-Jun Yue, Wei Wen Wong, Shao-Chong Lin, Tian-Li Guo, Si-Liang Li

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Content moderation assistance through image caption generation by Liam Kearns

“…In this work, a collaborative approach is taken, where a machine learning model is used to assist human moderators in the approval and rejection of media within a scavenger hunt game. …”
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Determinants of plasma poly- and perfluoroalkyl substances during pregnancy: The Japan Environment and Children’s Study by Yonghang Lai, Shoji F. Nakayama, Yukiko Nishihama, Tomohiko Isobe

“…This study investigated the determinants of PFAS in plasma collected from pregnant women enrolled in the Japan Environment and Children’s Study from 2011 to 2014. Several machine learning approaches were used, and the XGBoost model had the best predictive performance for seven PFAS quantified in more than 50 % of the population (from R2 = 0.34 and RMSE = 0.39 ng/mL for perfluorononanoic acid to R2 = 0.85 and RMSE = 0.19 ng/mL for perfluoroundecanoic acid). …”
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High-Precision Phenotyping in Soybeans: Applying Multispectral Variables Acquired at Different Phenological Stages by Celí Santana Silva, Dthenifer Cordeiro Santana, Fábio Henrique Rojo Baio, Ana Carina da Silva Cândido Seron, Rita de Cássia Félix Alvarez, Larissa Pereira Ribeiro Teodoro, Carlos Antônio da Silva Junior, Paulo Eduardo Teodoro

“…Remote sensing techniques and precision agriculture are being analyzed through research in different agricultural regions as a technological system aiming at productivity and possible low-cost reduction. Machine learning (ML) methods, together with the advent of demand for remotely piloted aircraft available on the market in the recent decade, have been conducive to remote sensing data processes. …”
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A heuristic-assisted deep reinforcement learning algorithm for flexible job shop scheduling with transport constraints by Xiaoting Dong, Guangxi Wan, Peng Zeng

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Impact of national e-commerce demonstration city pilot policy on urban carbon emission efficiency: From the perspective of soft and hard environments by YUE Li, WANG Xinran

“…[Methods] Based on prior research, this study employed multiple-period difference-in-differences and double machine learning models to rigorously identify the causal relationship between the NEDC pilot policy and urban CEE, using panel data of 282 prefecture-level administrative units in China from 2006 to 2022. …”
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Integrating radiomic texture analysis and deep learning for automated myocardial infarction detection in cine-MRI by Wang Xu, Xiangjiang Shi

“…A three-stage feature selection pipeline was employed, followed by classification using multiple machine learning models. Early and intermediate fusion strategies were integrated into the hybrid architecture. …”
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