Comprehensive analysis of methods for estimating actual paddy evapotranspiration—A review by Kiran Bala Behura, Sanjay Kumar Raul, Jagadish Chandra Paul, Sheelabhadra Mohanty, Prachi Pratyasha Jena, Sanat Kumar Dwibedi, Subhankar Ghosh, Laishram Kanta Singh, Sougrakpam Roma Devi, Arun Kumar Singha, Amulya Kumar Mohanty

“…Utilizing modernized technologies and hybrid models, the research investigation aims to deepen the understanding of ET variability for rice cropping systems to promote improved water resources management and sustainable agriculture practices as areas for future work suggest the application of vegetation indices incorporating high-resolution multi-spectral imagery to accurately estimate ET and appropriately differentiate between evaporation and transpiration in these complex agricultural systems.…”
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Quad-Tree-Based Driver Classification Using Deep Learning for Mild Cognitive Impairment Detection by Seyedeh Gol Ara Ghoreishi, Charles Boateng, Sonia Moshfeghi, Muhammad Tanveer Jan, Joshua Conniff, Kwangsoo Yang, Jinwoo Jang, Borko Furht, David Newman, Ruth Tappen, Monica Rosselli, Kelley L. Jackson

“…The experimental results demonstrate the effectiveness of the proposed algorithm, achieving an F1 score of 95% that significantly outperforms the baseline models. …”
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H-NMR metabolomics identifies three distinct metabolic profiles differentially associated with cardiometabolic risk in patients with obesity in the Di@bet.es cohort by Enrique Ozcariz, Montse Guardiola, Núria Amigó, Sergio Valdés, Wasima Oualla-Bachiri, Pere Rehues, Gemma Rojo-Martinez, Josep Ribalta

“…In addition, H-NMR metabolomics improved the prediction of future cardiometabolic disease in comparison with models relying on just anthropometric measures. …”
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Orchard-Wide Visual Perception and Autonomous Operation of Fruit Picking Robots: A Review by CHEN Mingyou, LUO Lufeng, LIU Wei, WEI Huiling, WANG Jinhai, LU Qinghua, LUO Shaoming

“…Enhanced strategies for effective fruit picking using the Eye-in-Hand system involve the development of more dexterous robotic hands and improved algorithms for precisely predicting the optimal picking point of each fruit. …”
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A comprehensive review of artificial intelligence approaches for smart grid integration and optimization by Malik Ali Judge, Vincenzo Franzitta, Domenico Curto, Andrea Guercio, Giansalvo Cirrincione, Hasan Ali Khattak

“…The advanced metaheuristic algorithms are a good addition to the literature, they are still in emerging stages and their performance can further be improved. …”
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Enhancing Security in DNP3 Communication for Smart Grids: A Segmented Neural Network Approach by Shahid Allah Bakhsh, Muhammad Shahbaz Khan, Oumaima Saidani, Nada Alasbali, S. Qasim Abbas, Muhammad Almas Khan, Jawad Ahmad

“…In CICFlowMeter3, the model achieved an accuracy of 99.86%, whereas, on the DNP3 Parser, it improved to 99.75%, demonstrating outstanding performance. …”
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Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens by Paul English, Muir J. Morrison, Blaine Mathison, Elizabeth Enrico, Ryan Shean, Brendan O'Fallon, Deven Rupp, Katie Knight, Alexandra Rangel, Jeffrey Gilivary, Amanda Vance, Haleina Hatch, Leo Lin, David P. Ng, Salika M. Shakir

“…By building on our work, researchers can develop better algorithms to improve the diagnosis of AFB, reducing the burden on laboratory staff and improving diagnostic speed and accuracy of these medically important organisms.…”
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Machine Learning–Based Prediction of Early Complications Following Surgery for Intestinal Obstruction: Multicenter Retrospective Study by Pinjie Huang, Jirong Yang, Dizhou Zhao, Taojia Ran, Yuheng Luo, Dong Yang, Xueqin Zheng, Shaoli Zhou, Chaojin Chen

“…A risk predictive model based on machine learning is helpful for early diagnosis and timely intervention. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…Balancing the characteristics of each channel further improves the accuracy of action recognition.Results and Discussion Comprehensive experiments are conducted on public datasets and in real-world environments to evaluate the effectiveness of the proposed model. …”
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Enhancing early gestational diabetes mellitus prediction with imputation-based machine learning framework: A comparative study on real-world clinical records by Leyao Ma, Lin Yang, Yaxin Wang, Jie Hao, Yini Li, Liangkun Ma, Ziyang Wang, Ye Li, Suhan Zhang, Mingyue Hu, Jiao Li, Yin Sun

“…Conclusion This study demonstrates the critical role of imputation in improving the performance and fairness of GDM prediction models. …”
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Aberrant gene expression prediction across human tissues by Florian R. Hölzlwimmer, Jonas Lindner, Georgios Tsitsiridis, Nils Wagner, Francesco Paolo Casale, Vicente A. Yépez, Julien Gagneur

“…Abstract Despite the frequent implication of aberrant gene expression in diseases, algorithms predicting aberrantly expressed genes of an individual are lacking. …”
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Sex estimation with ensemble learning: an analysis using anthropometric measurements of piriform aperture by Muhammed Emin Parlak, Yasin Etli, Murat Beyhan, Kubilay Kanat, Hüseyin Alper Kızıloğlu

“…Sex estimation results could be further improved with machine learning algorithms and especially with the ensemble learning method.…”
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Application of a modified set of GoogLeNet and ResNet-18 convolutional neural networks towards the identification of environmentally derived-MPLs in the Yadkin-pee dee river basin by Wesley Allen Williams, Anirudh Arunprasad, Shyam Aravamudhan

“…Irrespective of spectroscopic mode, marginal improvements in accuracy rates were seen, with the best improvements occurring in the Raman-based models (U[GN(FTIR), RN(Raman), GN(FTIR), and RN(Raman)]: 39, 42, 38.5, and 34.5; p-value: 1, .6753, .9719, and .4978). …”
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UAV as a Bridge: Mapping Key Rice Growth Stage with Sentinel-2 Imagery and Novel Vegetation Indices by Jianping Zhang, Rundong Zhang, Qi Meng, Yanying Chen, Jie Deng, Bingtai Chen

“…The optimal model, incorporating 300 features, achieved an F1 score of 0.864, representing a 2.5% improvement over models based on original spectral bands and a 38.8% improvement over models using a single feature. …”
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Simultaneous determination of 7 thiols associated proteins in lymphoma patients’serum and cerebrospinal fluid by UHPLC-HRMS technique by Qingkun Ma, Mei Zhang, Yongshuai Fan, Han Zhao, Kun Wang, Xiaojing Wang, Yanling Mu

“…Ultimately, this method greatly improves discrimination efficiency of model with accuracy of 98.83%. …”
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A Robust Framework for Bamboo Forest AGB Estimation by Integrating Geostatistical Prediction and Ensemble Learning by Lianjin Fu, Qingtai Shu, Cuifen Xia, Zeyu Li, Hailing He, Zhengying Li, Shaoyang Ma, Chaoguan Qin, Rong Wei, Qin Xiang, Xiao Zhang, Yiran Zhang, Huashi Cai

“…Subsequently, a stacked ensemble model, integrating four machine learning algorithms, predicted AGB from the full suite of continuous variables. …”
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A risk prediction system for depression in middle-aged and older adults grounded in machine learning and visualization technology: a cohort study by Jinsong Du, Jinsong Du, Jinsong Du, Xinru Tao, Le Zhu, Wenhao Qi, Xiaoqiang Min, Xiaoqiang Min, Hongyan Deng, Shujie Wei, Xiaoyan Zhang, Xiao Chang

“…This study innovatively proposed a visual risk prediction system for depressive symptoms and depression in middle-aged and older adults, rooted in machine learning and visualization technologies.MethodsUsing cohort data from the China Health and Retirement Longitudinal Study (CHARLS), involving 8,839 middle-aged and older adult participants, the study developed predictive models based on eight machine learning algorithms, primarily including LightGBM, XGBoost, and AdaBoost. …”
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Retrieval of Dissolved Organic Carbon Storage in Plateau Lakes Based on Remote Sensing and Analysis of Driving Factors: A Case Study of Lake Dianchi by Yufeng Yang, Wei Gao, Yuan Zhang

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Automated Root Cause Analysis of Network Failures in IP/MPLS Network Using Machine Learning and Case-Based Reasoning by Tikumporn Wankvar, Apichon Witayangkurn

“…Among the models evaluated, the SVM algorithm achieved the highest performance, with an F1-score of 0.969. …”
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Modernizing the Design Process for US Organ Allocation Policy: Toward a Continuous Distribution Policy for Kidneys by Elijah Pivo, PhD(c), James Alcorn, JD, Dimitris Bertsimas, PhD, Sarah E. Booker, MPH, Keighly Bradbrook, PhD, Thomas G. Dolan, MS, Lindsay V. Larkin, BA, Kayla R. Temple, BA, Nikolaos Trichakis, PhD

“…Methods. A new simulation algorithm was developed that reduces the time required to simulate 1 y of allocation from >6 h down to about 15 s while using the same simulation model as the preexisting simulator used by the Organ Procurement and Transplantation Network. …”
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