Locating Strong Electromagnetic Pulses Recorded by a Single Satellite with Cluster Analysis and Worldwide Lightning Location Network Observations by Zongxiang Li, Baofeng Cao, Wenjuan Zhang, Xiaoqiang Li, Xiong Zhang, Yongli Wei, Xiao Li, Changjiao Duan, Peng Li

“…The CAL method’s performance, influenced by the density-based spatial clustering of applications with noise (DBSCAN), the K-means, and the mean shift algorithms, is examined. Subsequently, an advanced version, mean shift denoised (MSDN)-CAL, is proposed, demonstrating marked improvements in location accuracy and reliability over the other CAL methods. …”
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Comparison of self-collected and healthcare worker-collected rectovaginal swabs for group B streptococcus detection in pregnancy using PCR with a commercial collection-enrichment d... by Iva Kukovica, Neža Omahen, Nika Klobučar, Martina Bučar, Anita Franko Rutar, Tina Perme, Tina Perme, Miha Lučovnik, Miha Lučovnik, Samo Jeverica, Samo Jeverica

“…Performance characteristics were calculated and compared between different diagnostics test algorithms using McNemar’s test for paired samples.ResultsOverall, GBS was detected in 18% (95% CI 13–23%; n = 40) of swabs A and 19% (95% CI 14–25%; n = 43) of swabs B. …”
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The effect of climate change on the distribution of Caspian red deer (Cervus elaphus maral) in Central Alborz Protected Area by Farid Salmanpour, Faraham Ahmadzadeh, Romina Sayyahnia, Bahram Hasanzade Kiabi

“…Also, presence and non-presence points of the species were collected random transects direct observation, as well as pictures of camera traps.Results and discussion: Using 19 climate parameters to evaluate habitat suitability in the future, it revealed that continuation of the climate change process in four optimistic to pessimistic scenarios using five MaxEnt, RF, ANN, GLM, MARS algorithms, the suitability of low altitude areas in the sectors of north and east will be reduced, and will be increased towards to highlands in southwest. …”
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Enhancing Transpiration Estimates: A Novel Approach Using SIF Partitioning and the TL-LUE Model by Tewekel Melese Gemechu, Baozhang Chen, Huifang Zhang, Junjun Fang, Adil Dilawar

“…Existing methodologies, including traditional techniques like the Penman–Monteith model, remote sensing approaches utilizing Solar-Induced Fluorescence (SIF), and machine learning algorithms, have demonstrated varying levels of effectiveness in ET estimation. …”
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Novel multiclass classification machine learning approach for the early-stage classification of systemic autoimmune rheumatic diseases by Feng Wang, Ting Wang, Wei Wei, Yun Wang, Xu Yuan, Renren Ouyang, Rujia Chen, Hongyan Hou, Shiji Wu

“…Clinical characteristics and laboratory markers were collected and nine key indicators, including anti-dsDNA, anti-SS-A60, anti-Sm/nRNP, antichromatin, anti-dsDNA (indirect immunofluorescence assay), haemoglobin (Hb), platelet, neutrophil percentage and cytoplasmic patterns (AC-19, AC-20), were selected for model building. Various ML algorithms were used to construct a tripartite classification ML model.Results Patients were divided into two cohorts, cohort 1 was used to construct a tripartite classification model. …”
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Synthesizing Local Capacities, Multi-Source Remote Sensing and Meta-Learning to Optimize Forest Carbon Assessment in Data-Poor Regions by Kamaldeen Mohammed, Daniel Kpienbaareh, Jinfei Wang, David Goldblum, Isaac Luginaah, Esther Lupafya, Laifolo Dakishoni

“…To improve forest carbon assessment, we employed stacked generalization, combining multiple machine learning algorithms to leverage their complementary strengths and address individual limitations. …”
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Pengukuran Performa Apache Spark dengan Library H2O Menggunakan Benchmark Hibench Berbasis Cloud Computing by Aminudin Aminudin, Eko Budi Cahyono

“…In order for Apache Spark to be able to do machine learning processes, in this paper an experiment will be conducted that integrates Apache Spark which acts as a large data processing environment and the concept of parallel computing will be combined with H2O libraries specifically for handling data processing using machine learning algorithms . Based on the results of testing Apache Spark in a cloud computing environment, Apache Spark is able to process weather data obtained from the largest weather data archive, namely NCDC data with data sizes up to 6GB. …”
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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…The scientific study of algorithms and statistical models are used by computer systems that use patterns and inference to perform tasks rather than using clear instructions. …”
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A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults by Daisu Abe, Motoki Inaji, Takeshi Hase, Eiichi Suehiro, Naoto Shiomi, Hiroshi Yatsushige, Shin Hirota, Shu Hasegawa, Hiroshi Karibe, Akihiro Miyata, Kenya Kawakita, Kohei Haji, Hideo Aihara, Shoji Yokobori, Takeshi Maeda, Takahiro Onuki, Kotaro Oshio, Nobukazu Komoribayashi, Michiyasu Suzuki, Taketoshi Maehara

“…Among several machine learning algorithms, eXtreme Gradient Boosting (XGBoost) demonstrated the highest predictive accuracy in cross-validation, with an AUROC of 0.81 (±0.07) and an AUPRC of 0.33 (±0.08). …”
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CYP3A5 promotes glioblastoma stemness and chemoresistance through fine-tuning NAD+/NADH ratio by Wentao Hu, Xiaoteng Cui, Hongyu Liu, Ze Li, Xu Chen, Qixue Wang, Guolu Zhang, Er Wen, Jinxin Lan, Junyi Chen, Jialin Liu, Chunsheng Kang, Ling Chen

“…Methods A multi-step process of machine learning algorithms was implemented to construct the glioma stemness-related score (GScore). …”
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Artificial intelligence-based prediction of second stage duration in labor: a multicenter retrospective cohort analysisResearch in context by Xiaoqing Huang, Xiaodan Di, Suiwen Lin, Minrong Yao, Suijin Zheng, Shuyi Liu, Wayan Lau, Zhixin Ye, Zilian Wang, Bin Liu

“…After the optimal features selected by recursive feature elimination (RFE) method, four ML algorithms were employed to build the models. The best model would be selected with the predictive performance and interpreted with Shapley Additive exPlanations method. …”
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A Hierarchical Machine Learning-Based Strategy for Mapping Grassland in Manitoba’s Diverse Ecoregions by Mirmajid Mousavi, James Kobina Mensah Biney, Barbara Kishchuk, Ali Youssef, Marcos R. C. Cordeiro, Glenn Friesen, Douglas Cattani, Mustapha Namous, Nasem Badreldin

“…This study developed a novel pixel-based grassland classification approach using three supervised machine learning (ML) algorithms, which were assessed in the province of Manitoba, Canada. …”
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Beyond identification of familial hypercholesterolemia: Improving downstream visits and treatments in a large health care system by Harin Lee, Tarun Kadaru, Ruth Schneider, Taylor Triana, Carol Tujardon, Colby Ayers, Mujeeb Basit, Zahid Ahmad, Amit Khera

“…Several electronic health record (EHR) algorithms have been developed to improve identification of patients with FH. …”
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Retinoblastoma. Part 2.  Treatment strategies for intraocular retinoblastoma by S.V. Ivanova, S.A. Kuleva, N.N. Sadovnikova, M.I. Komissarov, M.N. Chistyakova, A.V. Khokhlova, N.A. Shchegoleva

“…This paper discusses the algorithms to determine risk factors and further systemic treatment strategy in several large study groups. …”
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Calibración de cámaras de tiempo de vuelo: Ajuste adaptativo del tiempo de integración y análisis de la frecuencia de modulación by P. Gil, T. Kisler, G.J. García, C.A. Jara, J.A. Corrales

“…This method has been successfully tested on visual servoing algorithms with architecture âeye-in-handâ in which the sensory system consists of a ToF camera, in addition this methodology can be applied to other workspaces and scenarios. …”
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Defining hypoxaemia from pulse oximeter measurements of oxygen saturation in well children at low altitude in Bangladesh: an observational study by William Checkley, Amy Sarah Ginsburg, Tim Colbourn, Eric D McCollum, Salahuddin Ahmed, Nabidul H Chowdhury, Syed J R Rizvi, Holly B Schuh, Nazma Begum, Abdullah H Baqui, Carina King, Shubhada Hooli, Abu A M Hanif, Arunangshu D Roy, ASMD Ashraful Islam

“…If a higher threshold than <90% is adopted into LMIC care algorithms then decision-making using SpO2 must also consider the child’s clinical status to minimise misclassification of well children as hypoxaemic. …”
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Identification and verification of the optimal feature genes of ferroptosis in thyroid-associated orbitopathy by Xuemei Li, Xuemei Li, Xuemei Li, Xuemei Li, Xuemei Li, Chao Xiong, Chao Xiong, Chao Xiong, Chao Xiong, Chao Xiong, Siyi Wang, Siyi Wang, Siyi Wang, Zhangjun Ren, Zhangjun Ren, Zhangjun Ren, Qi Jin, Qi Jin, Qi Jin, Jinhai Yu, Jinhai Yu, Jinhai Yu, Jinhai Yu, Jinhai Yu, Yunxiu Chen, Yunxiu Chen, Yunxiu Chen, Puying Gan, Puying Gan, Puying Gan, Puying Gan, Qihua Xu, Qihua Xu, Qihua Xu, Qihua Xu, Qihua Xu, Yaohua Wang, Yaohua Wang, Yaohua Wang, Yaohua Wang, Yaohua Wang, Hongfei Liao, Hongfei Liao, Hongfei Liao, Hongfei Liao, Hongfei Liao

“…The intersection of DEGs, hub genes and ferroptosis-related gene yielded key genes of ferroptosis. Machine learning algorithms identified OFGs of ferroptosis. Meanwhile, by comparing the expression of FRGs in the orbital adipose tissue and the orbital fibroblasts (OFs) of healthy controls and TAO patients, as well as co-culturing macrophages and OFs in vitro, the influence of macrophages on FRGs in OFs was explored. …”
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The use of machine and deep learning to model the relationship between discomfort temperature and labor productivity loss among petrochemical workers by Yilin Zhang, Yifeng Chen, Qingling Su, Xiaoyin Huang, Qingyu Li, Yan Yang, Zitong Zhang, Jiake Chen, Zhihong Xiao, Rong Xu, Qing Zu, Shanshan Du, Wei Zheng, Weimin Ye, Jianjun Xiang

“…This study aimed to utilize machine learning (ML) and deep learning (DL) algorithms to quantify the impact of temperature discomfort on productivity loss among petrochemical workers and to identify key influencing factors. …”
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In-Season Automated Mapping of Xinjiang Cotton Based on Cumulative Spectral and Phenological Characteristics by Yongsheng Huang, Yaozhong Pan, Yu Zhu, Xiufang Zhu, Xingsheng Xia, Qiong Chen, Jufang Hu, Hongyan Che, Xuechang Zheng, Lingang Wang

“…Second, using the maximum between-class variance method (OTSU) and Sauvola algorithms, a new local adaptive threshold method (Otsu–Sauvola) was developed for the automatic determination of the classification threshold. …”
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Innovations in animal health: artificial intelligence-enhanced hematocrit analysis for rapid anemia detection in small ruminants by Aftab Siddique, Sudhanshu S. Panda, Sophia Khan, Seymone T. Dargan, Savana Lewis, India Carter, Jan A. Van Wyk, Ajit K. Mahapatra, Eric R. Morgan, Thomas H. Terrill

“…Using artificial intelligence-powered machine learning algorithms, an advanced, easy-to-use sensor was developed for rapidly alerting farmers as to low red blood cell count of their animals in this way to enable timely medical intervention. …”
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