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7. Conclusion
For several decades, AI has led to the development of operational applications in many fields, such as diagnostics and decision support with knowledge-based systems or neural networks, as well as pattern and speech recognition with stochastic models. The introduction of DNNs has made it possible to achieve unprecedented levels of performance, attracting unprecedented media coverage in virtually all sectors. As ever, transferring laboratory research to real-world applications requires substantial investment in time and money. There's a long way to go between an initial announcement and an actual marketed product. In medicine, in particular, the deployment of applications implies a complex evaluation mechanism, particularly in the clinical field. Finally, the success of an application implies genuine confidence in AI, as well as clear identification of responsibilities (cf. the autonomous...
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Conclusion
Bibliography
Reviews
AI Magazine (USA)
Artificial Intelligence (NL)
Bulletin of the AFIA, French Artificial Intelligence Association (F)
IEEE Transactions on Knowledge and Data Engineering (USA)
Journal of Intelligent Manufacturing (GB)
IEEE Transactions on Neural Networks and Learning Systems (USA)
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Websites
AFIA French AI Association : https://afia.asso.fr/
ECCAI European Coordinating Committee for Artificial Intelligence : https://eccai.org/
AAAI Association for the Advancement of Artificial Intelligence :
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