01812nas a2200253   4500000000100000000000100001008004100002260001200043653002500055653001600080653002100096653002100117653001500138653001000153100002600163700003800189700002500227245006500252856008200317300000900399490000600408520113000414022001401544       2020                            d  c12/202010aCoronavirus COVID-1910aData Mining10aMachine Learning10aImage Processing10aBiomarkers10aX-ray1 aSergio Muñoz Lezcano1 aFernando Carlos López Hernández1 aAlberto Corbi Bellot00aData Science Techniques for COVID-19 in Intensive Care Units  uhttps://www.ijimai.org/journal/sites/default/files/2020-11/ijimai_6_4_1_0.pdf  a8-170 v63 aData 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).  a1989-1660