Conference paper Open Access

Deep-Learning and HPC to Boost Biomedical Applications for Health (DeepHealth)

Monica Caballero; Jon Ander Gómez; Aimilia Bantouna

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Monica Caballero</dc:creator>
  <dc:creator>Jon Ander Gómez</dc:creator>
  <dc:creator>Aimilia Bantouna</dc:creator>
  <dc:description>The paper introduces the DeepHealth project: "Deep-Learning and HPC to Boost Biomedical Applications for Health". This project is funded by the European Commission under the H2020 framework program and aims to reduce the gap between the availability of mature enough AI-solutions and their deployment in real scenarios. Several existing software platforms provided by industrial partners will integrate state-of-the-art machine-learning algorithms and will be used for giving support to doctors in diagnosis, increasing their capabilities and efficiency. The DeepHealth consortium is composed by 21 partners from 9 European countries including hospitals, universities, large industry and SMEs.

This document is an accepted paper published using the Green Open Access Model. Published paper available at 

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  <dc:subject>libraries;europe;medical services;predictive models;medical diagnostic imaging;software</dc:subject>
  <dc:title>Deep-Learning and HPC to Boost Biomedical Applications for Health (DeepHealth)</dc:title>
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