https://www.socictopen.socict.org/files/original/ce9e51efa2f7c78b3c3e34a37ac4aef0.pdf b69eb407010a04911ff4749cb24bc69d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Data Science Techniques for COVID-19 in Intensive Care Units Creator An entity primarily responsible for making the resource Sergio Muñoz Lezcano, Fernando Carlos López Hernández, Alberto Corbi Bellot Description An account of the resource Data scientists aim to provide techniques and tools to the clinicians to manage the new coronavirus disease. Nowadays, new emerging tools based on Artificial Intelligence (AI), Image Processing (IP) and Machine Learning (ML) are contributing to the improvement of healthcare and treatments of different diseases. This paper reviews the most recent research efforts and approaches related to these new data driven techniques and tools in combination with the exploitation of the already available COVID-19 datasets. The tools can assist clinicians and nurses in efficient decision making with complex and heavily heterogeneous data, even in hectic and overburdened Intensive Care Units (ICU) scenarios. The datasets and techniques underlying these tools can help finding a more correct diagnosis. The paper also describes how these innovative AI+IP+ML-based methods (e.g., conventional X-ray imaging, clinical laboratory data, respiratory monitoring and automatic adjustments, etc.) can assist in the process of easing both the care of infected patients in ICUs and Emergency Rooms and the discovery of new treatments (drugs). Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource Biomarkers, machine learning, data mining, x-ray, Image Processing, coronavirus (COVID-19) Identifier An unambiguous reference to the resource within a given context 10.9781/ijimai.2020.11.008 Source A related resource from which the described resource is derived International Journal of Interactive Multimedia and Artificial Intelligence Publisher An entity responsible for making the resource available Universidad Internacional de La Rioja (UNIR) Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Technology