Search Results - "machines"

New Trends in Electrical Vehicle Powertrains

Subjects: “…reliability, electric vehicles, smart grid, adaptive control, wind energy, electrical machines…”
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Advances in Production Technology by Brecher, Christian

Subjects: “…Manufacturing, Machines, Tools…”
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DOAB: description of the publication

Advances in Production Technology by Brecher, Christian

Subjects: “…Manufacturing, Machines, Tools…”
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OAPEN Library: description of the publication

Identifying Potential Factors Associated With Racial Disparities in COVID-19 Outcomes: Retrospective Cohort Study Using Machine Learning on Real-World Data by Osama Dasa, Chen Bai, Ruba Sajdeya, Stephen E Kimmel, Carl J Pepine, Matthew J Gurka J, Reinhard Laubenbacher, Thomas A Pearson, Mamoun T Mardini

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Determining the Effect of Fear of Illness and Virus Evaluation and Quality of Life on Diagnosis of Social Phobia in Patients With Chronic Disease: Using Machine Learning Approaches by Faruk Erencan Balaban, Nihan Potas

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A Novel Machine Learning Framework for Comparison of Viral COVID-19-Related Sina Weibo and Twitter Posts: Workflow Development and Content Analysis by Chen, Shi, Zhou, Lina, Song, Yunya, Xu, Qian, Wang, Ping, Wang, Kanlun, Ge, Yaorong, Janies, Daniel

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Corrigendum: Predicting Colorectal Cancer Recurrence and Patient Survival Using Supervised Machine Learning Approach: A South African Population-Based Study by Okechinyere J. Achilonu, June Fabian, June Fabian, Brendan Bebington, Brendan Bebington, Elvira Singh, Elvira Singh, Gideon Nimako, Gideon Nimako, M. J. C. Eijkemans, Eustasius Musenge

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Comparison Between Statistical Model and Machine Learning Methods for Predicting the Risk of Renal Function Decline Using Routine Clinical Data in Health Screening by Cao X, Lin Y, Yang B, Li Y, Zhou J

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A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study by Cheng Fang, Yifeng Pan, Luotong Zhao, Zhaoyi Niu, Qingguo Guo, Bing Zhao

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Machine learning models of tobacco susceptibility and current use among adolescents from 97 countries in the Global Youth Tobacco Survey, 2013-2017 by Nayoung Kim, Wei-Yin Loh, Danielle E. McCarthy

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Comparing Learning Outcomes of Machine-Guided Virtual Reality-Based Training With Educator-Guided Training in a Metaverse Environment: Randomized Controlled Trial by Dilek Kitapcioglu, Mehmet Emin Aksoy, Arun Ekin Ozkan, Tuba Usseli

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Development and Validation of a Closed-Loop Functional Electrical Stimulation-Based Controller for Gait Rehabilitation Using a Finite State Machine Model by Naoki Hayami, Heather E. Williams, Koshi Shibagaki, Albert H. Vette, Yasuyuki Suzuki, Kimitaka Nakazawa, Taishin Nomura, Matija Milosevic

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Machine learning model demonstrates stunting at birth and systemic inflammatory biomarkers as predictors of subsequent infant growth - a four-year prospective study by Elizabeth Harrison, Sana Syed, Lubaina Ehsan, Najeeha T. Iqbal, Kamran Sadiq, Fayyaz Umrani, Sheraz Ahmed, Najeeb Rahman, Sadaf Jakhro, Jennie Z. Ma, Molly Hughes, S. Asad Ali

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Safeguarding Athletes Against Head Injuries Through Advances in Technology: A Scoping Review of the Uses of Machine Learning in the Management of Sports-Related Concussion by Anne Tjønndal, Stian Røsten

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A novel analytical framework for risk stratification of real‐world data using machine learning: A small cell lung cancer study by Luca Marzano, Adam S. Darwich, Salomon Tendler, Asaf Dan, Rolf Lewensohn, Luigi De Petris, Jayanth Raghothama, Sebastiaan Meijer

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Machine learning and dengue forecasting: Comparing random forests and artificial neural networks for predicting dengue burden at national and sub-national scales in Colombia. by Naizhuo Zhao, Katia Charland, Mabel Carabali, Elaine O Nsoesie, Mathieu Maheu-Giroux, Erin Rees, Mengru Yuan, Cesar Garcia Balaguera, Gloria Jaramillo Ramirez, Kate Zinszer

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Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis by Ruiqi Zhao, Sen Lin, Mengyao Han, Zhimei Lin, Mengjiao Yu, Bei Zhang, Lanyue Ma, Danfei Li, Lisheng Peng

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Making Metadata Machine-Readable as the First Step to Providing Findable, Accessible, Interoperable, and Reusable Population Health Data: Framework Development and Implementation Study by David Amadi, Sylvia Kiwuwa-Muyingo, Tathagata Bhattacharjee, Amelia Taylor, Agnes Kiragga, Michael Ochola, Chifundo Kanjala, Arofan Gregory, Keith Tomlin, Jim Todd, Jay Greenfield

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Identification of the high-risk area for schistosomiasis transmission in China based on information value and machine learning: a newly data-driven modeling attempt by Yan-Feng Gong, Ling-Qian Zhu, Yin-Long Li, Li-Juan Zhang, Jing-Bo Xue, Shang Xia, Shan Lv, Jing Xu, Shi-Zhu Li

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Machine learning models to predict outcomes at 30‐days using Global Leadership Initiative on Malnutrition combinations with and without muscle mass in people with cancer by Nicole Kiss, Belinda Steer, Marian de van derSchueren, Jenelle Loeliger, Roohallah Alizadehsani, Lara Edbrooke, Irene Deftereos, Erin Laing, Abbas Khosravi

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