You can download the proofs of concept developed by CIDAI members.
Successful POCs are the prelude to systematic AI adoption and an inspiring example of possible future applications in an organisation with greater success.
You can download the proofs of concept developed by CIDAI members.
Successful POCs are the prelude to systematic AI adoption and an inspiring example of possible future applications in an organisation with greater success.
Decision support systems in clinical care and health services management were identified as crucial in the fight against the COVID-19 pandemic. Our main goal is to develop a model based on recurrent neural networks (RNNs) that responds to the reality of hospitals during the pandemic. The goal for the model to generate daily predictions in a hospital setting that can be used as an early warning system and allow for proper management of existing resources.
In this document the focus is on the yellow container and the goal of the recycle plant in this case is to separate the incoming waste streams into a number of (sub)streams of a single kind. Every single stream is then transported to a specific plant for an even more specific treatment: cans will be used to manufacture new cans, bricks will be converted in aluminum foil and cupboard, plastics bottles will be used to manufacture new bottles and so on. The goal of this proposal extract higher purity fractions from recycling and waste streams using sensor based sorting.
Few works provide automatic support on the temporal evolution of pulmonary nodules. In this document, we present an end-to-end solution able to run asynchronous automatic pipeline analysis, to detect, quantify and predict nodules and their malignancy. Our system shows the results of the temporal analysis of pulmonary nodules in an intuitive and informative front-end interface, designed to support clinicians in their daily decision-making routine.
Encryption is a vital component of data privacy and security. A great deal of private information is transmitted online — including financial information and medical records — and it’s crucial to keep that information safe. We evaluated different methods of encryption and identified the most suitable for Machine learning applications: Homomorphic Encryption. Using this method, we can encrypt either a model or data.
The objective of this project is to create a simple system to recognise keywords and orders, capable of operating entirely locally; without depending at any time on an Internet connection or processing on external servers. The system is designed to work on home devices with limited resources and uses an artificial intelligence algorithm that can be trained to detect custom keywords.
With the implementation of this tool, a 24 x 7 service is made available to the educational community of the University of Girona (UdG) that automatically responds to the most frequent doubts about COVID-19 and the situation generated around this disease. The repertoire of topics from which answers are provided ranges from generic questions about COVID-19 to the steps of the university’s procedures, such as the opening of incidence or acquisition of protection material (EPIS), among others.
INSESS-COVID19 is a technology that allows to capture direct information from citizens in a short time, analyse and process it in a few minutes and generate executive reports directly formatted and prepared to be used in executive decision-making meetings. Depending on the nature of the information collection and the type of user questioned, the tool supports different types of decisions, from the most operational to the most strategic, including the definition of policies in any field. Developed in the context of COVID-19, it allows reacting quickly to the management of emergencies and disruptive situations with informed decisions.
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