Browsing Tyndall National Institute - Reports by Author "Gyrard, Amelie"
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- ItemAI for better health: AIOTI WG Health white paper(AIOTI -Alliance for IoT and Edge Computing Innovation, 2022-12-12) Dionisio, Pietro; Nikolov, Roumen; Gyrard, Amelie; Petelova, Katerina; Eberle, Wolfgang; Sanjuan Vinas, Lucas; San Segundo, Ruben; Tedesco, Salvatore; Andonegui, Cristina Martín; O’Murchu, CianThis white paper introduces the AIOTI WG Health vision and contribution to the European discussions on AI strategies applied to the health domain. The main aim of this paper is to contribute to the identification and addressing of any issues that might be hindering the wider adoption of AI technologies in the healthcare sector based on AIOTI WG Health’s members’ best practices. In conclusion: In the post-covid-19 era, the healthcare domain represents a unique opportunity for favouring the AI wider adoption. In fact, the healthcare domain is suffering a huge pressure due to internal and external massive changes that are pushing a development and a transformation of its dynamics. In this transformation process, AI can play a major role for smoothing the human and economic resources’ allocation and improving healthcare treatments management. According to this white paper, we believe that AI has an important role to play in the healthcare offerings of the future. Despite this, relevant challenges that have to be addressed. We tried to provide some answers to this challenges highlighting which is the AIOTI WG Health vision according to its members’ point of view. As addressed several times throughout the document, the greatest challenge to AI in the healthcare domains is not whether the technology will be capable enough to be useful, but rather ensuring its adoption in daily clinical practice overcoming barriers such as mistrust and scepticism. For widespread adoption to take place, AI systems must be approved by regulators, integrated with healthcare systems practices, standardised to a sufficient degree that similar products work in a similar fashion, taught to clinicians, paid for by public or private payer organisations. These challenges will ultimately be overcome, but time is needed. In Europe a strong push is encouraged towards AI adoption in daily practices, as testified by the key experiences included in the paper (ref. par. 9) but stronger alignment among EU member states, as well as within each country among the various decision making and legislative institutions, could further facilitate the AI wider adoption. As a result, we expect to see an ever more increasing use of AI in health daily practice within the next future connected to an increasing mingling with other AI application area such as smart cities and green economy.