Resultados de búsqueda - Random forest algorithms

An explainable machine learning model for comorbidity risk stratification in patients with fractures admitted to the intensive care unit: a multicenter study. por Liang, Xuelong, Zhao, Weijie, Liufu, Weigui, Qian, Jiale, Xiang, Nantian, Zhang, Xinzhe, Zhou, Jihui, Cui, Hongwang

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Using BERT models for breast cancer diagnosis from Turkish radiology reports. por Uskaner Hepsağ, Pınar, Özel, Selma Ayşe, Dalcı, Kubilay, Yazıcı, Adnan

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Disentangling Support for Violent and Non-violent Radicalization among Adolescents: A Latent Profile Analysis. por Miconi, Diana, Njingouo Mounchingam, Aoudou, Zambelli, Michela, Rousseau, Cécile

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Machine Learning Models to Predict Readmission Risk of Patients with Schizophrenia in a Spanish Region. por Góngora Alonso, Susel, Herrera Montano, Isabel, Ayala, Juan Luis Martín, Rodrigues, Joel J. P. C., Franco-Martín, Manuel, de la Torre Díez, Isabel

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The politics of problems versus solutions: Policymaking and grandstanding in congressional hearings. por Lewallen, Jonathan, Park, Ju Yeon, Theriault, Sean M.

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Predicting loss aversion behavior with machine-learning methods. por Saltık, Ömür, Rehman, Wasim ul, Söyü, Rıdvan, Değirmen, Süleyman, Şengönül, Ahmet

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Warmer climate threatens the occurrence of giant trees in the Amazon basin. por Borges de Lima, Robson, Pereira de Oliveira, Cinthia, da Silva, Diego Armando S., Granato-Souza, Daniela, Aparecida Gonçalves, Lorrayne, Vasconcelos, Caroline C., Batista, Anderson Pedro B., Ramos de Matos Filho, João, Gomes da Silva, Joselane P., da Silva Aparício, Perseu, Campelo de Souza, Carla S., Coelho de Abreu, Jadson, Correa Lopes, Iran Jorge, Ometto, Jean Pierre, Görgens, Eric Bastos

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Evaluation Methods for Breast Cancer Prediction in Machine Learning Field. por Zhang, Zirui, Li, Zixuan

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The Naples prognostic score as a nutritional and inflammatory biomarkers of stroke prevalence and all-cause mortality: insights from NHANES. por Zhao, Jin, Fan, Xingfu, Li, Xiaofang, Luo, Yang, Liu, Shiping

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Prognostic nutritional index and diabetic peripheral neuropathy in type 2 diabetes: a machine learning approach. por Wu, Ya, Dong, Danmeng, Liu, Yang, Xie, Xiaoyun

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Item reduction of the "Support Intensity Scale" for people with intellectual disabilities, using machine learning. por González‐Carrasco, Félix, Espinosa Parra, Felipe, Álvarez‐Aguado, Izaskun, Ponce Olguín, Sebastián, Vega Córdova, Vanessa, Roselló‐Peñaloza, Miguel

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Beware of Bear? Long-Term Spatio-Temporal Patterns of Human–Bear Conflict in Connecticut. por Berkowitz, Zachary, Bravo, Larissa Montas, Sen Roy, Shouraseni

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Machine learning-derived clinical decision algorithm for the diagnosis of hyperfunctioning parathyroid glands in patients with primary hyperparathyroidism. por Yeh, Randy, Kuo, Jennifer H., Huang, Bernice, Shobeiri, Parnian, Lee, James A., Tay, Yu-Kwang Donovan, Tabacco, Gaia, Bilezikian, John P., Dercle, Laurent

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Safety climate, safety behavior, injury experience, and musculoskeletal disorders among Iranian manufacturing employees: A structural equation modeling study. por Ghahramani, Abolfazl, Panahi, Saghar, Ebrahimi, Mahbob, Hajaghazadeh, Mohammad

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Development and validation of a CT based radiomics nomogram for preoperative prediction of ISUP/WHO grading in renal clear cell carcinoma. por Liu, Xiaohui, Han, Xiaowei, Wang, Xu, Xu, Kaiyuan, Wang, Mingliang, Zhang, Guozheng

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Influenza Vaccination of Nurses and Other Health Care Workers in Different Occupational Settings: A Classic and AI Mixed Approach for Time-to-Event Data. por Ratti, Matteo, Rescinito, Riccardo, Gigante, Domenico, Lontano, Alberto, Panella, Massimiliano

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Unlocking Dreams and Dreamless Sleep: Machine Learning Classification With Optimal EEG Channels. por Moctezuma, Luis Alfredo, Molinas, Marta, Abe, Takashi, Ardila, Carlos M.

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Applications of artificial intelligence in interventional oncology: An up-to-date review of the literature. por Matsui, Yusuke, Ueda, Daiju, Fujita, Shohei, Fushimi, Yasutaka, Tsuboyama, Takahiro, Kamagata, Koji, Ito, Rintaro, Yanagawa, Masahiro, Yamada, Akira, Kawamura, Mariko, Nakaura, Takeshi, Fujima, Noriyuki, Nozaki, Taiki, Tatsugami, Fuminari, Fujioka, Tomoyuki, Hirata, Kenji, Naganawa, Shinji

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Integrated analysis of gene expressions and targeted mirnas for explaining crosstalk between oral and esophageal squamous cell carcinomas through an interpretable machine learning... por Yadav, Khushi, Hasija, Yasha

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Random forest models of food safety behavior during the COVID-19 pandemic. por Berglund, Zachary, Kontor-Manu, Elma, Jacundino, Samuel Biano, Feng, Yaohua

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