Cambridge Social Dynamics Team
Thursday, 14 March 2019 from 16:00 to 17:00 (GMT)
Speaker: Alejandro Rodríguez-González
Cambridge, United Kingdom
Abstract:
Within the global endeavour of improving population health, one major challenge is the increasingly high cost associated with drug development. Drug repositioning, i.e. finding new uses for existing drugs, is a promising alternative; yet, its effectiveness has hitherto been hindered by our limited knowledge about diseases and their relationships. In this talk, I'll present DISNET, a web-based system designed to extract knowledge from signs and symptoms retrieved from medical databases and to enable the creation of customizable disease networks. Some of the main challenges that DISNET have addressed and some of the results obtained so far by the analysis of the information extracted until know with the help of DISNET will be also shown, as well as future directions.
Speaker Bio:
Alejandro Rodríguez-González, PhD, is an Associate Professor at the Department of Computer Languages and Systems and Software Engineering at Technical University of Madrid and the principal investigator of the Medical Data Analysis laboratory (MEDAL) at Center for Biomedical Technology. His main research interests are the Semantic Web, Artificial Intelligence and Biomedical informatics field, with an interest on the creation of Medical Diagnosis Systems, medical knowledge representation and the extraction of knowledge from different sources (text, social media, etc.) and the analysis of social media impact in e-Health. He is the current leader of DISNET project, which aims to create one of the largest existing networks of disease information to allow a better understanding of the diseases. Prof. Rodríguez was awarded in January 2018 with the “Best UPM Research Trajectory” award (2017 edition). Prof. Rodríguez is involved in several H2020 projects about Data Science and Big data in different domains, including skills definition, health sector and cyber physical products.
Cambridge, United Kingdom
Abstract:
Within the global endeavour of improving population health, one major challenge is the increasingly high cost associated with drug development. Drug repositioning, i.e. finding new uses for existing drugs, is a promising alternative; yet, its effectiveness has hitherto been hindered by our limited knowledge about diseases and their relationships. In this talk, I'll present DISNET, a web-based system designed to extract knowledge from signs and symptoms retrieved from medical databases and to enable the creation of customizable disease networks. Some of the main challenges that DISNET have addressed and some of the results obtained so far by the analysis of the information extracted until know with the help of DISNET will be also shown, as well as future directions.
Speaker Bio:
Alejandro Rodríguez-González, PhD, is an Associate Professor at the Department of Computer Languages and Systems and Software Engineering at Technical University of Madrid and the principal investigator of the Medical Data Analysis laboratory (MEDAL) at Center for Biomedical Technology. His main research interests are the Semantic Web, Artificial Intelligence and Biomedical informatics field, with an interest on the creation of Medical Diagnosis Systems, medical knowledge representation and the extraction of knowledge from different sources (text, social media, etc.) and the analysis of social media impact in e-Health. He is the current leader of DISNET project, which aims to create one of the largest existing networks of disease information to allow a better understanding of the diseases. Prof. Rodríguez was awarded in January 2018 with the “Best UPM Research Trajectory” award (2017 edition). Prof. Rodríguez is involved in several H2020 projects about Data Science and Big data in different domains, including skills definition, health sector and cyber physical products.
No hay comentarios:
Publicar un comentario