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| | date=2013-2015 | | | date=2013-2015 |
| | information= In this project, we will apply advanced computational and modelling strategies to clinical data sets (including both instrumentation data and text medical notes) in an effort to. 1) identify important factors or features that lead to unfavourable or favourable clinical conditions that determine if a patient should be released or not from that ICU with minimum risk of readmission; 2) Design specific decision models that will support clinician’s decisions in terms of releasing a patient form the ICU, in order to achieve more favourable clinical outcomes.}} | | | information= In this project, we will apply advanced computational and modelling strategies to clinical data sets (including both instrumentation data and text medical notes) in an effort to. 1) identify important factors or features that lead to unfavourable or favourable clinical conditions that determine if a patient should be released or not from that ICU with minimum risk of readmission; 2) Design specific decision models that will support clinician’s decisions in terms of releasing a patient form the ICU, in order to achieve more favourable clinical outcomes.}} |
| + | !style="vertical-align: top; text-align: left;"|{{Project2|logo=logo-inside.png |
| + | | shorttitle=INSIDE |
| + | | title= (Intelligent) Networked Robot Systems for Symbiotic Interaction with |
| + | Children with Impaired Development |
| + | | date=2014-2018 |
| + | | information= The INSIDE initiative explores symbiotic interactions between humans and robots in joint cooperative activities, and addresses the following key research problems: 1) How can robots plan their course of action to coordinate with and accommodate for the cooactions of their human teammates? |
| + | 2) How can task, context and environment information collected from a set of networked sensors be exploited to create more natural and engaging interactions between humans and robots involved in a joint cooperative activity in a physical environment? The proposed initiative involves the collaborative effort of the Computer Science Department at CMU and several Portuguese institutions (three research institutions and one hospital), as well as three Portuguese companies with extensive experience in the development of robot systems, human-computer speech interaction and compact biometric sensors.}} |
| |} | | |} |
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