The ubiquitous dissemination of intelligent systems is bound to transform society through a revolution that is already making an impact on science and technology. The merge of two large movements is responsible for such progress: on one hand the Big Data movement is making it possible for intelligent systems to execute complex tasks based on machine learning applied to lots of data, mostly structured. The need to handle and interpret non-structured data, such as text, is perhaps the main obstacle for the full realization of intelligent systems. This is precisely the focus of the second movement, namely the development of natural language processing on which a more efficient learning by the machines depends. In chemistry and materials science, for instance, machine learning and Big Data have been exploited in materials and drug discovery, to develop Internet-of-Things applications and in the analysis of sensing data. In this presentation, examples will be given of artificial intelligence applications for semi-automated literature surveys in materials discovery and in computer-assisted clinical diagnosis. The specific case of health monitoring illustrates the leveraging of materials science and artificial intelligence. While materials sciences are key to create the devices that provide the data to feed the intelligent systems, machine learning and other artificial intelligence strategies are used to interpret the sensing data for the end application.<br/>

Materials science in the era of artificial intelligence

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.