Enhancing proximal and remote sensing of soil organic carbon: A local modelling approach guided by spectral and spatial similarities by Qi Sun, Pu Shi

“…Here, we propose a local learning approach that searches spectrally and spatially similar samples for site-specific SOC predictive modelling. …”
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Robust and Unified Semi-Supervised Unmixing of Hyperspectral Imaging for Linear and Multilinear Models by Daniel Ulises Campos-Delgado, Juan Nicolas Mendoza-Chavarria, Omar Gutierrez-Navarro, Laura Quintana-Quintana, Raquel Leon, Samuel Ortega, Himar Fabelo, Carlos Lopez, Marylene Lejeune, Gustavo M. Callico

“…In this work, we derive closed-solutions at each step of the CCDO scheme, and just for the multilinear model, the end-members estimation involves a gradient descent scheme with optimal linear search. We validate first our contributions with synthetic HS images that include Gaussian and sparse noise components to evaluate their robustness, and compare them with supervised and unsupervised perspectives. …”
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Prehospital critical care beyond advanced life support for out-of-hospital cardiac arrest: A systematic review by Adam J. Boulton, Rachel Edwards, Andrew Gadie, Daniel Clayton, Caroline Leech, Michael A. Smyth, Terry Brown, Joyce Yeung

“…Prehospital critical care was defined as any provider with enhanced clinical competencies beyond standard advanced life support algorithms and dedicated dispatch to critically ill patients. …”
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Predictive analysis of clinical features for HPV status in oropharynx squamous cell carcinoma: A machine learning approach with explainability by Emily Diaz Badilla, Ignasi Cos, Claudio Sampieri, Berta Alegre, Isabel Vilaseca, Simone Balocco, Petia Radeva

“…Materials and Methods:: We employed the RADCURE dataset clinical information to train six Machine Learning algorithms, evaluating them via cross-validation for grid search hyper-parameter tuning and feature selection as well as a final performance measurement on a 20% sample test set. …”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…This study underscores the importance of spatial context in corn yield prediction and lays the foundation for future research across diverse agricultural settings, focusing on optimizing neighborhood size, integrating spatial and spectral data, and refining spatial dependencies through localized search algorithms.…”
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Integrated DDPG-PSO energy management systems for enhanced battery cycling and efficient grid utilization by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Wen Yao Low, Nor Zaihar Yahaya, Ahmed Tijjani Dahiru, Temitope Ibrahim Amosa, Shehu Lukman Ayinla

“…Cost evaluations under critical peak tariffs indicate that both EMS algorithms achieved a 34 % cost saving compared to a grid-only system. …”
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Traditional and machine learning models for predicting haemorrhagic transformation in ischaemic stroke: a systematic review and meta-analysis by Yanan Wang, Zengyi Zhang, Zhimeng Zhang, Xiaoying Chen, Junfeng Liu, Ming Liu

“…Methods PubMed and Ovid-Embase were searched for observational studies or randomised controlled trials related to traditional or machine learning-based models. …”
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Target determination for transcranial magnetic stimulation in patients with a pharmacotherapy-resistant depressive episode based on the individual parameters of resting-state funct... by A. G. Poydasheva, D. O. Sinitsyn, I. S. Bakulin, N. A. Suponeva, N. V. Maslennikov, E. E. Tsukarzi, S. N. Mosolov, M. A. Piradov

“…The investigation can be considered to be pilot in searching for algorithms to enhance the efficiency of rTMS DLPFC in pharmacotherapy-resistant depression using the algorithm for personification of target selection. …”
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Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis by Jinxi Yang, Siyao Zeng, Shanpeng Cui, Junbo Zheng, Hongliang Wang

“…MethodsWe performed a search across 6 electronic databases for studies developing ML predictive models for ARDS, with a cutoff date of December 29, 2024. …”
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Opportunities and Challenges of Cardiovascular Disease Risk Prediction for Primary Prevention Using Machine Learning and Electronic Health Records: A Systematic Review by Tianyi Liu, Andrew J. Krentz, Zhiqiang Huo, Vasa Ćurčin

“…A systematic literature search was performed in March 2024, encompassing the Medline and Embase databases, to identify studies published since 2010. …”
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Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration by Maoqiang Lin, Maoqiang Lin, Shaolong Li, Yabin Wang, Yabin Wang, Guan Zheng, Guan Zheng, Fukang Hu, Fukang Hu, Qiang Zhang, Qiang Zhang, Pengjie Song, Haiyu Zhou, Haiyu Zhou

“…Subsequently, four machine learning algorithms (SVM-RFE, Random Forest, XGB, and GLM) were used to select the method to construct the diagnostic model. …”
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The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review by Yuchen Ma, Mohan Li, Huiqun Wu

“…ObjectiveWe evaluated the diagnostic value of ML models constructed using radiomic features extracted from CCTA in predicting MACEs, and compared the performance of different learning algorithms and models, thereby providing clinical recommendations for the diagnosis, treatment, and prognosis of MACEs. …”
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Accuracy evaluation of dental CBCT and scanned model registration method based on pulp horn mapping surface: an in vitro proof-of-concept by Dianhao Wu, Jingang Jiang, Jinke Wang, Shan Zhou, Kun Qian

“…The small surface with adjustable parameters is reconstructed near the mapping point of the crown, and the new matching point pairs between the point and the mapping surface are searched. The sparse iterative closest point (ICP) algorithm is used to solve the new matching point pairs. …”
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In-vitro diagnostic point-of-care tests in paediatric ambulatory care: A systematic review and meta-analysis. by Oliver Van Hecke, Meriel Raymond, Joseph J Lee, Philip Turner, Clare R Goyder, Jan Y Verbakel, Ann Van den Bruel, Gail Hayward

“…HIV-POCTs improved initiating earlier antiretroviral therapy compared to usual care (RR, 3.11; 95% CI [1.55 to 6.25], n = 912). …”
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Exploring fecal microbiota signatures associated with immune response and antibiotic impact in NSCLC: insights from metagenomic and machine learning approaches by Wenjie Han, Wenjie Han, Yuhang Zhou, Yuhang Zhou, Yiwen Wang, Yiwen Wang, Xiaolin Liu, Tao Sun, Tao Sun, Junnan Xu, Junnan Xu, Junnan Xu

“…Among eight machine learning algorithms evaluated, the optimal model was selected to construct a predictive framework for immunotherapy response.ResultsMicrobial α-diversity was significantly elevated in responders compared to non-responders, with antibiotic administration further amplifying this difference—most notably at the species level. …”
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Machine Learning for Non-Destructive Prediction of Sunflower Leaf Area by Joao Everthon da Silva Ribeiro, Antonio Gideilson Correia da Silva, Pablo Henrique de Almeida Oliveira, Josiana Micarla da Silva Oliveira, Alessandra Nunes da Silva, John Victor Lucas Lima, Ivan Euzebio da Silva, Ester Dos Santos Coelho, Isaque de Oliveira Leite, Elania Freire da Silva, Toshik Iarley da Silva, Lindomar Maria da Silveira, Aurelio Paes Barros Junior

“…Therefore, the present study aimed to develop and compare linear regression models and machine learning algorithms for the non-destructive prediction of leaf area in four sunflower cultivars (BRS 323, Altis 99, Sany 66, and BRS 442). …”
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Large-area urban TomoSAR method with limited a priori knowledge and a complex deep learning model by Haoxuan Duan, Yuzhou Liu, Hong Zhang, Peifeng Ma, Zhongqi Shi, Zihuan Guo, Yixian Tang, Fan Wu, Chao Wang

“…Additionally, the computational inefficiency of existing algorithms significantly hinders the large-scale practical deployment of TomoSAR. …”
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PD-L1 expression predicts the efficacy of PD-1 blockade plus chemotherapy versus chemotherapy alone in treatment-naïve advanced or metastatic gastric cancer: a pooled analysis of r... by Wei Zhou, Zeng-Zhi Cai, Zhuolin Fan, Xu Zheng, Yu-Tong Chen

“…Randomized controlled trials (RCTs) have demonstrated that combining Programmed Cell Death Protein-1 (PD-1) blockade with chemotherapy significantly improves overall survival (OS) compared to chemotherapy alone. However, the efficacy of PD-1 inhibitors in patients with low Programmed Cell Death-Ligand 1 (PD-L1) expression remains unclear.MethodsElectronic databases were searched for RCTs comparing PD-1/PD-L1 inhibitors plus chemotherapy to placebo plus chemotherapy or chemotherapy alone in treatment-naïve advanced gastric or gastroesophageal junction adenocarcinoma patients. …”
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Large Language Model–Assisted Risk-of-Bias Assessment in Randomized Controlled Trials Using the Revised Risk-of-Bias Tool: Usability Study by Jiajie Huang, Honghao Lai, Weilong Zhao, Danni Xia, Chunyang Bai, Mingyao Sun, Jianing Liu, Jiayi Liu, Bei Pan, Jinhui Tian, Long Ge

“…MethodsWe systematically searched the Cochrane Library (through October 2023) for reviews using RoB2, categorized by interest in adhering or assignment. …”
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Network and systems biology approaches help investigate gene regulatory interactions between Salmonella disease and host in chickens: Model‐based in silico evidence combined with g... by Reza Tohidi, Hoda Javaheri Bargourooshi, Arash Javanmard

“…Based on this information, this report searches for resistance and susceptibility lineages in most genomic regions for SE. …”
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