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Forging Connections in Latin America to Advance AI in Radiology.

Felipe Campos KitamuraFelipe Barjud Pereira do NascimentoGuillermo Elizondo-RojasHernán ChavesHéctor Henríquez LeightonEmmanuel Salinas-MirandaThiago JúlioAntonio Jose da RochaCésar Higa Nomura
Published in: Radiology. Artificial intelligence (2022)
The 1° Encontro Latino-Americano de IA em Saúde (1st Latin American Meeting on AI in Health) was held during the 2022 Jornada Paulista de Radiologia, the annual radiology meeting in the state of São Paulo. The event was created to foster discussion among Latin American countries about the complexity, challenges, and opportunities in developing and using artificial intelligence (AI) in those countries. Technological improvements in AI have created high expectations in health care. AI is recognized increasingly as a game changer in clinical radiology. To counter the fear that AI would "take over" radiology, the program included activities to educate radiologists. The development of AI in Latin America is in its early days, and although there are some pioneer cases, many regions still lack world-class technological infrastructure and resources. Legislation, regulation, and public policies in data privacy and protection, digital health, and AI are recent advances in many countries. The meeting program was developed with a broad scope, with expertise from different countries, backgrounds, and specialties, with the objective of encompassing all levels of complexity (from basic concepts to advanced techniques), perspectives (clinical, technical, ethical, and business), and specialties (both informatics and data science experts and the usual radiology clinical groups). It was an opportunity to connect with peers from other countries and share lessons learned about AI in health care in different countries and contexts. Keywords: Informatics, Use of AI in Education, Impact of AI on Education, Social Implications © RSNA, 2022.
Keyphrases
  • artificial intelligence
  • big data
  • healthcare
  • machine learning
  • deep learning
  • public health
  • mental health
  • quality improvement
  • emergency department
  • risk assessment
  • social media
  • adverse drug