Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Mark, Michalski"'
Publikováno v:
Zeszyty Naukowe Małopolskiej Wyższej Szkoły Ekonomicznej w Tarnowie, Vol 47, Iss 3, Pp 87-104 (2020)
Service providers, including business insurance, are looking for solutions to offer services of the best possible quality, including an assessment of that quality. For this reason, the attempt to apply the Gap Model was to demonstrate how other metho
Externí odkaz:
https://doaj.org/article/7224c3a2467642c384d67f9d4a4457f1
Autor:
Micha Sam Brickman, Raredon, Clark, Fisher, Paul M, Heerdt, Robert B, Schonberger, Alyssa, Nargi, Steven, Nivison, Elaine, Fajardo, Ranjit, Deshpande, Shamsuddin, Akhtar, Allison M, Greaney, Joseph, Belter, Thomas, Raredon, Joseph, Zinter, Andrew, McKee, Mark, Michalski, Pavlina, Baevova, Laura E, Niklason
Publikováno v:
Anesthesia & Analgesia. 134:1094-1105
The coronavirus disease 2019 (COVID-19) pandemic has revealed that even the best-resourced hospitals may lack sufficient ventilators to support patients under surge conditions. During a pandemic or mass trauma, an affordable, low-maintenance, off-the
Autor:
Mehdi, Djekidel, Mark, Michalski
Publikováno v:
Journal of Nuclear Medicine Technology. 50:179-181
Splenosis, commonly occurs incidentally and locates to bowel surfaces, parietal peritoneum, mesentery, and diaphragm, but can potentially occur anywhere in the peritoneal cavity. Patients frequently have a history of splenectomy or trauma. On the oth
Autor:
Mark Michalski
Publikováno v:
Science, Faith, the Sacred, and the Question of Evil: The Inception of World in Leibniz, Husserl, and Hölderlin. 37:267-277
Publikováno v:
Zeszyty Naukowe Uniwersytetu Przyrodniczo-Humanistycznego w Siedlcach. Seria: Administracja i Zarządzanie. 50:55-64
The aim of this research was to indicate the possibilities of using synthetic measure to find and analyse spatial disparities of the natural environment in 102 diagnostic communities of the Świętokrzyskie Voivodeship as a peripheral area. The resea
Autor:
Markus D Herrmann, David A Clunie, Andriy Fedorov, Sean W Doyle, Steven Pieper, Veronica Klepeis, Long P Le, George L Mutter, David S Milstone, Thomas J Schultz, Ron Kikinis, Gopal K Kotecha, David H Hwang, Katherine P Andriole, A John Iafrate, James A Brink, Giles W Boland, Keith J Dreyer, Mark Michalski, Jeffrey A Golden, David N Louis, Jochen K Lennerz
Publikováno v:
Journal of Pathology Informatics, Vol 9, Iss 1, Pp 37-37 (2018)
Background: Digital Imaging and Communications in Medicine (DICOM®) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been
Externí odkaz:
https://doaj.org/article/d0f634989b4f4163b8669fb2c90130e7
Publikováno v:
Journal of the American College of Radiology. 16:1351-1356
Recent advances in artificial intelligence (AI) are providing an opportunity to enhance existing clinical decision support (CDS) tools to improve patient safety and drive value-based imaging. We discuss the advantages and potential applications that
Wie verhält sich das menschliche Sein zur Zeit? Besitzt jeder Mensch einen substantiellen Kern, der bei allem Wechsel akzidenteller Eigenschaften unverändert bleibt? Ist jeder Mensch eigentlich immer nur in der Gegenwart, während seine Herkunft ni
Autor:
Neil A. Tenenholtz, Lina Chen, Felipe Kitamura, John E. Kirsch, Katherine P. Andriole, Bernardo Bizzo, Mark Michalski, Christopher P. Bridge, Romane Gauriau
Publikováno v:
J Digit Imaging
The growing interest in machine learning (ML) in healthcare is driven by the promise of improved patient care. However, how many ML algorithms are currently being used in clinical practice? While the technology is present, as demonstrated in a variet
Autor:
Dong Yang, Daguang Xu, Holger R. Roth, Alvin Ihsani, Varun Buch, Mark Michalski, Sean Doyle, Andriy Myronenko, Neil A. Tenenholtz
Publikováno v:
Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges ISBN: 9783030390730
STACOM@MICCAI
STACOM@MICCAI
We propose a 4D convolutional neural network (CNN) for the segmentation of retrospective ECG-gated cardiac CT, a series of single-channel volumetric data over time. While only a small subset of volumes in the temporal sequence is annotated, we define
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adc2f7425306519a89bb465d7a923f6e
https://doi.org/10.1007/978-3-030-39074-7_8
https://doi.org/10.1007/978-3-030-39074-7_8