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Relevant bibliographies by topics / Medical Machines / Books

Books on the topic 'Medical Machines'

To see the other types of publications on this topic, follow the link: Medical Machines.

Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Robert, Bud, Finn Bernard S. 1932-, and Trischler Helmuth, eds. Manifesting medicine: Bodies and machines. Amsterdam, the Netherlands: Harwood Academic, 1999.

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2

1973-, Johnson Ericka, and Berner Boel, eds. Technology and medical practice: Blood, guts and machines. Farnham: Ashgate, 2009.

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3

Biohybrid systems: Nerves, interfaces, and machines. Weinheim: Wiley-VCH, 2011.

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4

Bueltzingsloewen, Isabelle von. Machines à instruire, machines à guérir: Les hôpitaux universitaires et la médicalisation de la société allemande (1730-1850). Lyon: Presses universitaires de Lyon, 1997.

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5

An empire of machines: The rise and consequences of technological medicine. Cambridge: Cambridge University Press, 2009.

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6

Tjora, Aksel Hagen. Caring machines: Emerging practices of work and coordination in the use of medical emergency communication technology. Trondheim: Faculty of Social Sciences and Technology Management, Norwegian University of Science and Technology, 1997.

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7

Lobanov, Aleksey. Medical and biological bases of safety. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1439619.

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The textbook considers the subject and tasks of the discipline, highlights the medical and biological foundations of ensuring human security in the conditions of natural, man-made and biological-social emergencies, as well as when using modern weapons of destruction by a probable enemy. Briefly, but quite informative, the structure of the human body and the basics of its functioning are described. The specificity and mechanism of the toxic effect of harmful substances on a person, the energy effect and the combined effect of the main damaging factors of the sources of emergency situations of peacetime and wartime are shown. The article highlights the medical and biological aspects of ensuring the safe life of people in adverse environmental conditions, including in regions with hot and cold climates (the Arctic). The methods of forecasting and assessing the medical situation in emergency zones and lesions are presented. The means and methods of medical and biological protection and first aid to the affected are shown. The main tasks and organizational structure of formations and institutions of the medical rescue service of the GO, the All-Russian Service of Disaster Medicine and medical formations of the EMERCOM of Russia are considered. Organizational issues of medical and biological protection in emergency situations are highlighted. The features of the organization of medical support for those affected by terrorist attacks are considered. It is intended for students and cadets of educational institutions of higher education studying under the bachelor's degree program in the following areas of training: "Technosphere security", "Infocommunication technologies and communication systems", "Information systems and technologies", "State and municipal management", "Economics", "Mechatronics and robotics", "Operation of transport and technological machines and complexes", "Informatics and computer engineering", "Air Navigation", "System analysis and management". It can also be useful for researchers and a wide range of specialists engaged in practical work on planning and organizing medical and biological protection of the population.

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8

The body electric: How strange machines built the modern American. New York: New York University Press, 2003.

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9

van Rysewyk, Simon Peter, and Matthijs Pontier, eds. Machine Medical Ethics. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08108-3.

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10

Rivalland, Paul. It's more than machines and medicine: They should understand, there's a Yan̲angu way : summary report : a short report ... on the activities of Western Desert Nganampa Walytja Palyantjaku Tjutaku. Casuarina, N.T: Cooperative Research Centre for Aboriginal Health, 2006.

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11

Lian, Chunfeng, Xiaohuan Cao, Islem Rekik, Xuanang Xu, and Pingkun Yan, eds. Machine Learning in Medical Imaging. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87589-3.

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12

Shi, Yinghuan, Heung-Il Suk, and Mingxia Liu, eds. Machine Learning in Medical Imaging. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00919-9.

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13

Bhatia, Kanwal, and Herve Lombaert, eds. Machine Learning Meets Medical Imaging. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27929-9.

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14

Wang, Li, Ehsan Adeli, Qian Wang, Yinghuan Shi, and Heung-Il Suk, eds. Machine Learning in Medical Imaging. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47157-0.

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15

Suzuki, Kenji, Fei Wang, Dinggang Shen, and Pingkun Yan, eds. Machine Learning in Medical Imaging. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24319-6.

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16

Wang, Qian, Yinghuan Shi, Heung-Il Suk, and Kenji Suzuki, eds. Machine Learning in Medical Imaging. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67389-9.

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17

Liu, Mingxia, Pingkun Yan, Chunfeng Lian, and Xiaohuan Cao, eds. Machine Learning in Medical Imaging. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59861-7.

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18

Wang, Fei, Pingkun Yan, Kenji Suzuki, and Dinggang Shen, eds. Machine Learning in Medical Imaging. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15948-0.

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19

Wang, Fei, Dinggang Shen, Pingkun Yan, and Kenji Suzuki, eds. Machine Learning in Medical Imaging. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35428-1.

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20

Wu, Guorong, Daoqiang Zhang, and Luping Zhou, eds. Machine Learning in Medical Imaging. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10581-9.

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21

Zhou, Luping, Li Wang, Qian Wang, and Yinghuan Shi, eds. Machine Learning in Medical Imaging. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24888-2.

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22

Wu, Guorong, Daoqiang Zhang, Dinggang Shen, Pingkun Yan, Kenji Suzuki, and Fei Wang, eds. Machine Learning in Medical Imaging. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02267-3.

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23

Suk, Heung-Il, Mingxia Liu, Pingkun Yan, and Chunfeng Lian, eds. Machine Learning in Medical Imaging. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32692-0.

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24

Lian, Chunfeng, Xiaohuan Cao, Islem Rekik, Xuanang Xu, and Zhiming Cui, eds. Machine Learning in Medical Imaging. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-21014-3.

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25

European Organization for Nuclear Research. Proton-ion medical machine study: PIMMS. Geneva: CERN, 2000.

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26

Haq, Nandinee, Patricia Johnson, Andreas Maier, Tobias Würfl, and Jaejun Yoo, eds. Machine Learning for Medical Image Reconstruction. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88552-6.

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27

Haq, Nandinee, Patricia Johnson, Andreas Maier, Chen Qin, Tobias Würfl, and Jaejun Yoo, eds. Machine Learning for Medical Image Reconstruction. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17247-2.

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28

Deeba, Farah, Patricia Johnson, Tobias Würfl, and Jong Chul Ye, eds. Machine Learning for Medical Image Reconstruction. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61598-7.

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29

Knoll, Florian, Andreas Maier, Daniel Rueckert, and Jong Chul Ye, eds. Machine Learning for Medical Image Reconstruction. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33843-5.

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30

Knoll, Florian, Andreas Maier, and Daniel Rueckert, eds. Machine Learning for Medical Image Reconstruction. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00129-2.

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31

Bhattacharyya, Siddhartha, Debanjan Konar, Jan Platos, Chinmoy Kar, and Kalpana Sharma, eds. Hybrid Machine Intelligence for Medical Image Analysis. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-8930-6.

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32

Medieval identity machines. Minneapolis: University of Minnesota Press, 2003.

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33

Bates, Erica M. The health machine: The impact of medical technology. Ringwood, Australia: Penguin Books, 1985.

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34

Al-Turjman, Fadi, and Anand Nayyar, eds. Machine Learning for Critical Internet of Medical Things. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-80928-7.

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35

Reyes, Mauricio, Pedro Henriques Abreu, and Jaime Cardoso, eds. Interpretability of Machine Intelligence in Medical Image Computing. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-17976-1.

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36

Lindeen, Carol K. Ambulances (Mighty Machines). Capstone Press, 2005.

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37

Manifesting medicine: Bodies and machines. Australia: Harwood Academic, 1999.

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38

Mattern, Joanne. X-Ray Machines. Scholastic Library Publishing, 2015.

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39

X-Ray Machines. Scholastic Library Publishing, 2015.

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40

Johnson, Ericka, and Boel Berner. Technology and Medical Practice: Blood, Guts and Machines. Taylor & Francis Group, 2016.

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41

Science of Medical Technology: Machines, Vaccines and Healthcare. Book House, 2019.

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42

Johnson, Ericka, and Boel Berner. Technology and Medical Practice: Blood, Guts and Machines. Taylor & Francis Group, 2016.

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43

Johnson, Ericka, and Boel Berner. Technology and Medical Practice: Blood, Guts and Machines. Taylor & Francis Group, 2016.

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44

Rooney, Anne. Machines in Medicine (Cutting Edge Medicine). World Almanac Library, 2007.

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45

Klingel, Cynthia Fitterer, and Gary M. Amoroso. Ambulances (Machines at Work). Child's World, 2007.

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46

(Editor), Vladimir Uversky, and Irina A. Kataeva (Editor), eds. Cellulosome (Molecular Anatomy and Physiology of Proteinaceous Machines). Nova Science Publishers, 2006.

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47

Jung, Ranu. Biohybrid Systems: Nerves, Interfaces and Machines. Wiley & Sons, Incorporated, John, 2013.

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48

Amirian, Pouria, Trudie Lang, and Francois van Loggerenberg. Big Data in Healthcare: Extracting Knowledge from Point-of-Care Machines. Springer, 2017.

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49

Ethics, Medicine, and Information Technology: Intelligent Machines and the Transformation of Health Care. Cambridge University Press, 2016.

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50

Goodman, Kenneth W. Ethics, Medicine, and Information Technology: Intelligent Machines and the Transformation of Health Care. Cambridge University Press, 2015.

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