Doctor AI

Doctor AI: Predicting Clinical Events via Recurrent Neural Networks

Leveraging large historical data in electronic health record (EHR), we developed Doctor AI, a generic predictive model that covers observed medical conditions and medication uses. Doctor AI is a temporal model using recurrent neural networks (RNN) and was developed and applied to longitudinal time stamped EHR data from 260K patients over 8 years. Encounter records (e.g. diagnosis codes, medicat...

AI-Complete, AI-Hard, or AI-Easy - Classification of Problems in AI

The paper contributes to the development of the theory of AI-Completeness by formalizing the notion of AIComplete and AI-Hard problems. The intended goal is to provide a classification of problems in the field of General Artificial Intelligence. We prove Turing Test to be an instance of an AI-Complete problem and further show numerous AI problems to be AI-Complete or AI-Hard via polynomial time...

"Doctor".

VUB AI - lab team VUB - AI - lab

The VUB AI-lab team is mainly interested in the two loosely linked aspects of on-board control and heterogeneity. One major effort for forstering both aspects within RoboCup’s small robots league is our development of a so-to-say robot constructionkit, allowing to implement a wide range of players with onboard control. For the ’99 competition, the existing RoboCube controller-hardware has been ...

AI Magazine Poster: The AI Landscape

remained unsung beyond the AI community. AI’s integration into the fabric of everyday life has had tremendous impact, but the public may not recognize its many roles or understand its fundamental goals. In response, AI Magazine has developed a poster to help educate students, faculty, and the public about AI and to spur them to find out more about the field. The poster’s design was based on inp...