Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective... by Seok Jun Park, Seungwon Yang, Suhyun Lee, Sung Hwan Joo, Taemin Park, Dong Hyun Kim, Hyeonji Kim, Soyun Park, Jung-Tae Kim, Won Gun Kwack, Sung Wook Kang, Yun-Kyoung Song, Jae Myung Cha, Sang Youl Rhee, Eun Kyoung Chung

“…Among the tested ML algorithms, random forest achieved the highest accuracy (area under the receiver operating characteristic curve [AUROC] 0.88 for both cohorts). …”
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Combining UAV Remote Sensing with Ensemble Learning to Monitor Leaf Nitrogen Content in Custard Apple (<i>Annona squamosa</i> L.) by Xiangtai Jiang, Lutao Gao, Xingang Xu, Wenbiao Wu, Guijun Yang, Yang Meng, Haikuan Feng, Yafeng Li, Hanyu Xue, Tianen Chen

“…This study uses an ensemble learning technique based on multiple machine learning algorithms to effectively and precisely monitor the leaf nitrogen content in the tree canopy using multispectral canopy footage of custard apple trees taken via Unmanned Aerial Vehicle (UAV) across different growth phases. …”
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Intracranial aneurysm instability prediction model based on 4D-Flow MRI and HR-MRI by Fei Peng, Jiaxiang Xia, Fandong Zhang, Shiyu Lu, Hao Wang, Jiashu Li, Xinmin Liu, Yao Zhong, Jiahuan Guo, Yonghong Duan, Binbin Sui, Chuyang Ye, Yi Ju, Shuai Kang, Yizhou Yu, Xin Feng, Xingquan Zhao, Rui Li, Aihua Liu

“…We introduce a specialized ensemble learning framework, termed the Hybrid Model, which synergistically combines two heterogeneous base learning algorithms: 4D-Flow logistic regression (4D-Flow-LR) and Multi-crop Attention Branch Network (MicroAB-Net). …”
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Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

“…We compare various KD algorithms to identify the technique that produces a smaller model with the modest accuracy drop. …”
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Modelling the seasonal dynamics of Aedes albopictus populations using a spatio-temporal stacked machine learning model by Daniele Da Re, Giovanni Marini, Carmelo Bonannella, Fabrizio Laurini, Mattia Manica, Nikoleta Anicic, Alessandro Albieri, Paola Angelini, Daniele Arnoldi, Federica Bertola, Beniamino Caputo, Claudio De Liberato, Alessandra della Torre, Eleonora Flacio, Alessandra Franceschini, Francesco Gradoni, Përparim Kadriaj, Valeria Lencioni, Irene Del Lesto, Francesco La Russa, Riccardo Paolo Lia, Fabrizio Montarsi, Domenico Otranto, Gregory L’Ambert, Annapaola Rizzoli, Pasquale Rombolà, Federico Romiti, Gionata Stancher, Alessandra Torina, Enkelejda Velo, Chiara Virgillito, Fabiana Zandonai, Roberto Rosà

“…The choice of the modeling approach, i.e., the algorithm, is itself a significant source of variability, as different algorithms applied to the same dataset can yield disparate outcomes. …”
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Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review by Claire R. van Genugten, Claire R. van Genugten, Melissa S. Y. Thong, Melissa S. Y. Thong, Melissa S. Y. Thong, Wouter van Ballegooijen, Wouter van Ballegooijen, Wouter van Ballegooijen, Annet M. Kleiboer, Annet M. Kleiboer, Donna Spruijt-Metz, Arnout C. Smit, Mirjam A. G. Sprangers, Mirjam A. G. Sprangers, Yannik Terhorst, Yannik Terhorst, Heleen Riper, Heleen Riper, Heleen Riper

“…To accomplish this, JITAIs often apply complex analytic techniques, such as machine learning or Bayesian algorithms to real- or near-time data acquired from smartphones and other sensors. …”
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Implementasi Algoritma Catboost Dan Shapley Additive Explanations (SHAP) Dalam Memprediksi Popularitas Game Indie Pada Platform Steam by Mohammad Teddy Syamkalla, Siti Khomsah, Yohani Setya Rafika Nur

“…Previous research has tried to use logistic regression and random forest algorithms to forecast the popularity of indie games on the Steam platform, However, the model results using various methods are still low. …”
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Epidemiological aspects of nephrolithiasis and chronic diseases of the cardiovascular system combination by R. V. Royuk, S. K. Yarovoy, N. A. Guseva, Sh. L. Voskanyan, V. V. Royuk, D. B. Rodin

“…The presence chronic cardiovascular diseases (CVD), especially complicated by congestive heart failure in patients with first time revealed nephrolithiasis, implies changes in the algorithms of metaphylactic of nephrolithiasis (regime of water loads, selection of diuretics and anticoagulants).…”
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Lipids as key biomarkers in unravelling the pathophysiology of obesity-related metabolic dysregulation by Anis Adibah Osman, Siok-Fong Chin, Lay-Kek Teh, Noraidatulakma Abdullah, Nor Azian Abdul Murad, Rahman Jamal

“…Metabolites were identified using a molecular feature and chemical formula algorithm, followed by a differential analysis using MetaboAnalyst 5.0. …”
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Assessment of prognosis and responsiveness to immunotherapy in colorectal cancer patients based on the level of immune cell infiltration by Kaili Liao, Minqi Zhu, Lei Guo, Zijun Gao, Jinting Cheng, Bing Sun, Yihui Qian, Bingying Lin, Jingyan Zhang, Tingyi Qian, Yixin Jiang, Yanmei Xu, Qionghui Zhong, Xiaozhong Wang

“…Immunotherapy sensitivity analysis was performed using CIBERSORT and TIMER algorithms. Gene biofunction analysis was performed using Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA). …”
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Development of a Predictive Model of Occult Cancer After a Venous Thromboembolism Event Using Machine Learning: The CLOVER Study by Anabel Franco-Moreno, Elena Madroñal-Cerezo, Cristina Lucía de Ancos-Aracil, Ana Isabel Farfán-Sedano, Nuria Muñoz-Rivas, José Bascuñana Morejón-Girón, José Manuel Ruiz-Giardín, Federico Álvarez-Rodríguez, Jesús Prada-Alonso, Yvonne Gala-García, Miguel Ángel Casado-Suela, Ana Bustamante-Fermosel, Nuria Alfaro-Fernández, Juan Torres-Macho

“…XGBoost, LightGBM, and CatBoost algorithms were used to train different prediction models, which were subsequently validated in a hold-out dataset. …”
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MASFNet: Multi-level attention and spatial sampling fusion network for pine wilt disease trees detection by Dong Ren, Meng Li, Ziyu Hong, Li Liu, Jingfeng Huang, Hang Sun, Shun Ren, Pan Sao, Wenbin Wang, Jingcheng Zhang

“…However, due to the diversity of object information in UAV remote sensing images, most existing algorithms are prone to confusing the background environment and difficult to distinguish highly similar ground objects, resulting in a lot of false detections. …”
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Association between estimated glucose disposal rate and cardiovascular diseases in patients with diabetes or prediabetes: a cross-sectional study by Jinhao Liao, Linjie Wang, Lian Duan, Fengying Gong, Huijuan Zhu, Hui Pan, Hongbo Yang

“…Three machine learning methods (SVM-RFE, XGBoost, and Boruta algorithms) were employed to select the most critical variables. …”
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Modeling Climate‐Driven Vegetation Changes Under Contrasting Temperate and Arid Conditions in the Mediterranean Basin by Marco Bianchini, Mohamed Tarhouni, Matteo Francioni, Marco Fiorentini, Chiara Rivosecchi, Jamila Msadek, Abderrazak Tlili, Farah Chouikhi, Marina Allegrezza, Giulio Tesei, Paola Antonia Deligios, Roberto Orsini, Luigi Ledda, Maria Karatassiou, Athanasios Ragkos, Paride D'Ottavio

“…MaxEnt emerged as the most reliable algorithm for small presence‐only datasets, effectively predicting habitat suitability. …”
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COSMIC’s Large-scale Search for Technosignatures during the VLA Sky Survey: Survey Description and First Results by C. D. Tremblay, J. Sofair, L. Steffes, T. Myburgh, D. Czech, P. B. Demorest, R. A. Donnachie, A. W. Pollak, M. Ruzindana, Siemion A. P. V., S. S. Varghese, S. Z. Sheikh

“…Developing algorithms to search through data efficiently is a challenging part of searching for signs of technology beyond our solar system. …”
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Machine learning for predicting neoadjuvant chemotherapy effectiveness using ultrasound radiomics features and routine clinical data of patients with breast cancer by Pu Zhou, Pu Zhou, Hongyan Qian, Pengfei Zhu, Jiangyuan Ben, Jiangyuan Ben, Guifang Chen, Qiuyi Chen, Lingli Chen, Jia Chen, Ying He, Ying He

“…The clinical feature prediction model using the GBM algorithm had an AUC of 0.819 and an accuracy of 0.739. …”
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Proximity-based solutions for optimizing autism spectrum disorder treatment: integrating clinical and process data for personalized care by Annarita Vignapiano, Annarita Vignapiano, Francesco Monaco, Francesco Monaco, Stefania Landi, Luca Steardo, Carlo Mancuso, Claudio Pagano, Gianvito Petrillo, Alessandra Marenna, Martina Piacente, Stefano Leo, Carminia Marina Ingenito, Rossella Bonifacio, Benedetta Di Gruttola, Marco Solmi, Marco Solmi, Marco Solmi, Marco Solmi, Maria Pontillo, Giorgio Di Lorenzo, Giorgio Di Lorenzo, Alessio Fasano, Alessio Fasano, Alessio Fasano, Giulio Corrivetti, Giulio Corrivetti

“…A central data hub, the Master Data Plan (MDP), will aggregate and analyze information from diverse sources, feeding AI algorithms that can identify risk factors for ASD, personalize treatment plans based on individual needs, and even predict potential relapses. …”
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Remote sensing-based maize growth process parameters revel the maize yield: a comparison of field- and regional-scale by Minghan Cheng, Xiuliang Jin, Chenwei Nie, Kaihua Liu, Tianao Wu, Yuping Lv, Shuaibing Liu, Xun Yu, Yi Bai, Yadong Liu, Lin Meng, Xiao Jia, Yuan Liu, Lili Zhou, Fei Nan

“…However, most previous studies have relied on remote sensing data from one or a few periods for yield estimation, thus lacking a comprehensive description of entire crop growth. Furthermore, past algorithms have not considered their applicability across different observational scales (e.g., unmanned aerial vehicle (UAV)- and satellite-observed). …”
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Diagnosis and Treatment of Patients with Autoimmune Hepatitis (Experts’ Agreement) by Yu. G. Sandler, E. V. Vinnitskaya, K. L. Raikhelson, K. V. Ivashkin, S. N. Batskikh, E. N. Aleksandrova, D. T. Abdurakhmanov, D. I. Abdulganieva, I. G. Bakulin, A. O. Bueverov, S. L. Vorobyev, O. A. Gerasimova, A. I. Dolgushina, M. S. Zhuravleva, L. Yu. Ilchenko, V. E. Karev, N. V. Korochanskaya, I. L. Kliaritskaia, N. S. Karnaukhov, S. V. Lapin, M. A. Livzan, M. V. Maevskaya, N. V. Marchenko, T. P. Nekrasova, I. G. Nikitin, A. A. Novikov, R. G. Saifutdinov, E. V. Skazyvaeva, V. E. Syutkin, M. K. Prashnova, T. Yu. Khaymenova, S. G. Khomerik

“…This publication presents the main discussion points of the agreement regarding methods and algorithms for detecting autoantibodies, the role of liver biopsy, revised morphological criteria for AIH, optimized immunosuppressive therapy regimens, updated criteria for assessing the response to therapy.Conclusions. …”
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Evidence-based clinical standard for the diagnosis and treatment of candidemia in critically ill patients in the intensive care unit by Jorge Alberto Cortés, Martha Carolina Valderrama-Rios, Paula M. Peçanha-Pietrobom, Moacyr Silva Júnior, Cándida Diaz-Brochero, Rafael Ricardo Robles-Torres, Carmelo José Espinosa-Almanza, Laura Cristina Nocua-Báez, Marcio Nucci, Carlos Arturo Álvarez-Moreno, Flavio Queiroz-Telles, Ricardo Rabagliati, Rita Rojas-Fermín, Jorge L. Finquelievich, Fernando Riera, Patricia Cornejo-Juárez, Dora E. Corzo-León, Luis E. Cuéllar, Jeannete Zurita, Augusto Raúl Hernández, Arnaldo Lopes Colombo

“…This evidence-based clinical standard, established through expert consensus for the Latin American context, contains recommendations and algorithms for diagnosing and treating candidemia in critically ill ICU patients.…”
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