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Remote Collaboration, Decision Support, and On-Demand Medical Image Analysis for Acute Stroke Care

Abstract : Acute stroke is the leading cause of disabilities and the fourth cause of death worldwide. The treatment of stroke patients often requires fast collaboration between medical experts and fast analysis and sharing of large amounts of medical data, especially image data. In this situation, cloud technologies provide a potentially cost-effective way to optimize management of stroke patients and, consequently, improve patient outcome. This paper presents a cloud-based platform for Medical Distributed Utilization of Services & Applications (MEDUSA). This platform aims at improving current acute care settings by allowing fast medical data exchange, advanced processing of medical image data, automated decision support, and remote collaboration between physicians in a secure and responsive virtual space. We describe a prototype implemented in the MEDUSA platform for supporting the treatment of acute stroke patients. As the initial evaluation illustrates, this prototype improves several aspects of current stroke care and has the potential to play an important role in the care management of acute stroke patients.
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https://hal.inria.fr/hal-01757577
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Renan Barros, Jordi Borst, Steven Kleynenberg, Céline Badr, Rama-Rao Ganji, et al.. Remote Collaboration, Decision Support, and On-Demand Medical Image Analysis for Acute Stroke Care. 4th European Conference on Service-Oriented and Cloud Computing (ESOCC), Sep 2015, Taormina, Italy. pp.214-225. ⟨hal-01757577⟩

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