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Federico Cabitza

Showing results (51-60 of 91) with videos related to

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Frontiers in Medicine|May 7, 2019
The Revival of the Notes Field: Leveraging the Unstructured Content in Electronic Health RecordsMichela Assale, Linda Greta Dui, Andrea Cina, et al.
Journal of Shoulder and Elbow Surgery|June 30, 2009
Infectious and thromboembolic complications of arthroscopic shoulder surgeryPietro Randelli, Alessandro Castagna, Federico Cabitza, et al.
Clinical Chemistry and Laboratory Medicine|August 1, 2021
The multicenter European Biological Variation Study (EuBIVAS): a new glance provided by the Principal Component Analysis (PCA), a machine learning unsupervised algorithms, based on the basic metabolic panel linked measurandsAnna Carobene, Andrea Campagner, Christian Uccheddu, et al.
Diagnostics (Basel, Switzerland)|March 29, 2023
Assessment of Fast-Track Pathway in Hip and Knee Replacement Surgery by Propensity Score Matching on Patient-Reported OutcomesAndrea Campagner, Frida Milella, Stefania Guida, et al.
Journal of Medical Systems|July 2, 2020
Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility StudyDavide Brinati, Andrea Campagner, Davide Ferrari, et al.
Health Informatics Journal|August 14, 2019
Data work in healthcare: An IntroductionClaus Bossen, Kathleen H Pine, Federico Cabitza, et al.
Recenti Progressi in Medicina|February 23, 2023
[Artificial intelligence applied to the electrocardiogram.]Federico Cabitza, Fabrizio Ammirati, Manuela Bocchino, et al.
Artificial Intelligence in Medicine|March 29, 2024
Never tell me the odds: Investigating pro-hoc explanations in medical decision makingFederico Cabitza, Chiara Natali, Lorenzo Famiglini, et al.
Health Informatics Journal|January 23, 2019
The elephant in the record: On the multiplicity of data recording workFederico Cabitza, Angela Locoro, Camilla Alderighi, et al.
Computers in Biology and Medicine|June 23, 2020
Assessment and prediction of spine surgery invasiveness with machine learning techniquesAndrea Campagner, Pedro Berjano, Claudio Lamartina, et al.
Pageof 10

Showing results (51-60 of 91) with videos related to

Sort By:
Pageof 10
Frontiers in Medicine|May 7, 2019
The Revival of the Notes Field: Leveraging the Unstructured Content in Electronic Health RecordsMichela Assale, Linda Greta Dui, Andrea Cina, et al.
Journal of Shoulder and Elbow Surgery|June 30, 2009
Infectious and thromboembolic complications of arthroscopic shoulder surgeryPietro Randelli, Alessandro Castagna, Federico Cabitza, et al.
Clinical Chemistry and Laboratory Medicine|August 1, 2021
The multicenter European Biological Variation Study (EuBIVAS): a new glance provided by the Principal Component Analysis (PCA), a machine learning unsupervised algorithms, based on the basic metabolic panel linked measurandsAnna Carobene, Andrea Campagner, Christian Uccheddu, et al.
Diagnostics (Basel, Switzerland)|March 29, 2023
Assessment of Fast-Track Pathway in Hip and Knee Replacement Surgery by Propensity Score Matching on Patient-Reported OutcomesAndrea Campagner, Frida Milella, Stefania Guida, et al.
Journal of Medical Systems|July 2, 2020
Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility StudyDavide Brinati, Andrea Campagner, Davide Ferrari, et al.
Health Informatics Journal|August 14, 2019
Data work in healthcare: An IntroductionClaus Bossen, Kathleen H Pine, Federico Cabitza, et al.
Recenti Progressi in Medicina|February 23, 2023
[Artificial intelligence applied to the electrocardiogram.]Federico Cabitza, Fabrizio Ammirati, Manuela Bocchino, et al.
Artificial Intelligence in Medicine|March 29, 2024
Never tell me the odds: Investigating pro-hoc explanations in medical decision makingFederico Cabitza, Chiara Natali, Lorenzo Famiglini, et al.
Health Informatics Journal|January 23, 2019
The elephant in the record: On the multiplicity of data recording workFederico Cabitza, Angela Locoro, Camilla Alderighi, et al.
Computers in Biology and Medicine|June 23, 2020
Assessment and prediction of spine surgery invasiveness with machine learning techniquesAndrea Campagner, Pedro Berjano, Claudio Lamartina, et al.
Pageof 10