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1دورية أكاديمية
المؤلفون: Stephan Sloth Lorenzen, Mads Nielsen, Espen Jimenez-Solem, Tonny Studsgaard Petersen, Anders Perner, Hans-Christian Thorsen-Meyer, Christian Igel, Martin Sillesen
المصدر: Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
وصف الملف: electronic resource
Relation: https://doaj.org/toc/2045-2322
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المؤلفون: Zhongfeng Kang, Mads Nielsen, Bo Yang, Lihui Deng, Stephan Sloth Lorenzen
المصدر: Expert Systems with Applications. 212:118738
مصطلحات موضوعية: Artificial Intelligence, General Engineering, Computer Science Applications
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المؤلفون: Mads Nielsen, Hans-Christian Thorsen-Meyer, Anders Perner, Stephan Sloth Lorenzen, Martin Sillesen, Tonny Studsgaard Petersen, Espen Jimenez-Solem, Christian Igel
المصدر: Scientific Reports
Lorenzen, S S, Nielsen, M, Jimenez-Solem, E, Petersen, T S, Perner, A, Thorsen-Meyer, H-C, Igel, C & Sillesen, M 2021, ' Using machine learning for predicting intensive care unit resource use during the COVID-19 pandemic in Denmark ', Scientific Reports, vol. 11, no. 1, 18959 . https://doi.org/10.1038/s41598-021-98617-1
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)مصطلحات موضوعية: Critical Care, Computer science, Science, medicine.medical_treatment, Denmark, Machine learning, computer.software_genre, Risk Assessment, Article, law.invention, Machine Learning, law, Risk Factors, Intensive care, Virology, medicine, Humans, Pandemics, Retrospective Studies, Mechanical ventilation, Multidisciplinary, Ventilators, Mechanical, Receiver operating characteristic, business.industry, SARS-CoV-2, COVID-19, Computational Biology, Retrospective cohort study, Intensive care unit, Respiration, Artificial, Hospitals, Computational biology and bioinformatics, Hospitalization, Intensive Care Units, ROC Curve, Area Under Curve, Ventilation (architecture), Medicine, Resource allocation, Artificial intelligence, Risk assessment, business, computer, Forecasting
وصف الملف: application/pdf
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المؤلفون: Ninh Pham, Stephan Sloth Lorenzen
المصدر: IJCAI
مصطلحات موضوعية: Product (mathematics), Sampling (statistics), Geometry, Wedge (geometry), GeneralLiterature_MISCELLANEOUS, Mathematics
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::8b5e69f47f0abf89131934369d9c30e2
https://doi.org/10.24963/ijcai.2021/652 -
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المصدر: Wu, Y-S, Masegosa, A, Lorenzen, S S, Igel, C & Seldin, Y 2021, Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote . in Advances in Neural Information Processing Systems (NeurIPS 2021) . vol. 34, Thirty-fifth Conference on Neural Information Processing Systems-NeurIPS 2021, 06/12/2021 . < https://proceedings.neurips.cc/paper/2021/hash/69386f6bb1dfed68692a24c8686939b9-Abstract.html >
University of Copenhagenمصطلحات موضوعية: FOS: Computer and information sciences, Machine Learning, Computer Science - Machine Learning, Majority Vote, PAC-Bayesian, Statistics - Machine Learning, ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION, MathematicsofComputing_NUMERICALANALYSIS, TheoryofComputation_GENERAL, Machine Learning (stat.ML), Ensemble Methods, Machine Learning (cs.LG)
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9387c162dd73fec6af0a01654c0c747a
https://vbn.aau.dk/da/publications/2b14b130-cd23-4fd1-b655-9418de9e9f57 -
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المؤلفون: Tonny Studsgaard Petersen, Espen Jimenez-Solem, Martin Sillesen, Anders Perner, Stephan Sloth Lorenzen, Christian Igel, Hans-Christian Thorsen-Meyer, Mads Nielsen
المصدر: SSRN Electronic Journal.
مصطلحات موضوعية: education.field_of_study, business.industry, Population, Vital signs, Declaration, Retraining, Machine learning, computer.software_genre, Intensive care unit, law.invention, Patient safety, Resource (project management), law, Health care, Medicine, Artificial intelligence, business, education, computer
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::10efa0d4dcae071ae5db445676edea57
https://doi.org/10.2139/ssrn.3796914 -
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المؤلفون: Stephan Sloth Lorenzen, Ninh Pham
المصدر: Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676575
ECML/PKDD (1)مصطلحات موضوعية: Speedup, Computer science, Sampling (statistics), 02 engineering and technology, Wedge (geometry), GeneralLiterature_MISCELLANEOUS, Task (computing), symbols.namesake, 020204 information systems, Product (mathematics), 0202 electrical engineering, electronic engineering, information engineering, symbols, 020201 artificial intelligence & image processing, Hardware_REGISTER-TRANSFER-LEVELIMPLEMENTATION, Algorithm, Gibbs sampling
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::298bdd927b2d8abd3ed967a6a8cb8ca0
https://doi.org/10.1007/978-3-030-67658-2_25 -
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المؤلفون: Akshay Pai, Jens E.V. Petersen, Benjamin Skov Kaas-Hansen, Marie Helleberg, Matilde Winther-Jensen, Andreas David Lauritzen, Raghavendra Selvan, Gert Mehl Virenfeldt, Stine Hasling Mogensen, Mads Nielsen, Martin Erik Nyeland, Mikkel Bonde, Martin Sillesen, Hans-Christian Thorsen-Meyer, Janne Petersen, Martin Lillholm, Casper Worm Hansen, Christian Igel, Christina Lioma, Bulat Ibragimov, Anders Perner, Stephan Sloth Lorenzen, Mikkel Zöllner Ankarfeldt, Jon Middleton, Allan Linneberg, Espen Jimenez-Solem, Alexander Bonde, Abraham George Smith, Oswin Krause, Christian Hansen, Tonny Studsgaard Petersen, Mostafa Mehdipour Ghazi, Marleen de Bruijne, Nicki Skafte Detlefsen, Wouter Boomsma
المساهمون: Radiology & Nuclear Medicine
المصدر: Jimenez-Solem, E, Petersen, T S, Hansen, C, Hansen, C, Lioma, C, Igel, C, Boomsma, W, Krause, O, Lorenzen, S, Selvan, R, Petersen, J, Nyeland, M E, Ankarfeldt, M Z, Virenfeldt, G M, Winther-Jensen, M, Linneberg, A, Ghazi, M M, Detlefsen, N, Lauritzen, A D, Smith, A G, de Bruijne, M, Ibragimov, B, Petersen, J, Lillholm, M, Middleton, J, Mogensen, S H, Thorsen-Meyer, H-C, Perner, A, Helleberg, M, Kaas-Hansen, B S, Bonde, M, Bonde, A, Pai, A, Nielsen, M & Sillesen, M 2021, ' Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients ', Scientific Reports, vol. 11, no. 1, 3246 . https://doi.org/10.1038/s41598-021-81844-x
Scientific Reports
Scientific Reports, 11(1):3246. Nature Publishing Group
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)مصطلحات موضوعية: Male, medicine.medical_treatment, Disease, Comorbidity, 030204 cardiovascular system & hematology, law.invention, Body Mass Index, Machine Learning, 0302 clinical medicine, law, Risk Factors, 030212 general & internal medicine, Prospective Studies, Prospective cohort study, Aged, 80 and over, Multidisciplinary, Computational science, Area under the curve, Age Factors, Middle Aged, Prognosis, Intensive care unit, Biobank, Hospitalization, Intensive Care Units, Cohort, Hypertension, Medicine, Infectious diseases, Female, medicine.symptom, medicine.medical_specialty, Critical Care, Science, Article, 03 medical and health sciences, Sex Factors, medicine, Humans, Computer Simulation, Aged, Mechanical ventilation, business.industry, Organ dysfunction, COVID-19, medicine.disease, Respiration, Artificial, ROC Curve, Emergency medicine, business, Body mass index
وصف الملف: application/pdf
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المصدر: University of Copenhagen
Masegosa, A R, Lorenzen, S S, Igel, C & Seldin, Y 2020, Second Order PAC-Bayesian Bounds for the Weighted Majority Vote . in Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual . NeurIPS Proceedings, Advances in Neural Information Processing Systems, vol. 33, 34th Conference on Neural Information Processing System (NeurIPS 2020), Virtuak, 06/12/2020 . < https://proceedings.neurips.cc/paper/2020/file/386854131f58a556343e056f03626e00-Paper.pdf >مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, Machine Learning (stat.ML), Machine Learning (cs.LG)
وصف الملف: application/pdf
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f53996f234fd39e982f600d10d02409d
http://arxiv.org/abs/2007.13532 -
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المؤلفون: Stephan Sloth Lorenzen, niklas Hjuler, stephen alstrup
المصدر: University of Copenhagen
مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Computers and Society, Computer Science - Machine Learning, Statistics - Machine Learning, Computers and Society (cs.CY), Machine Learning (stat.ML), Machine Learning (cs.LG)
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f43444f8ca414235e8f6df6b3fb18d5
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