Advancements and Challenges in Regulating AI-Based Software as Medical Devices: Current Perspectives and Future Implications

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The use of artificial intelligence (AI) and machine learning (ML) is generating a significant transformation of the healthcare sector worldwide. These technologies are improving the efficiency of workflows, increasing the accuracy of diagnoses and raising the quality of patient treatment. However, t...

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Detalles Bibliográficos
Autor: Chuco Aguilar, Victoria Judith
Formato: artículo
Fecha de Publicación:2024
Institución:Escuela de Posgrado Newman
Repositorio:Revistas - Escuela de Posgrado Newman
Lenguaje:español
OAI Identifier:oai:ojs.pkp.sfu.ca:article/327
Enlace del recurso:https://journals.epnewman.edu.pe/index.php/IBJ/article/view/327
Nivel de acceso:acceso abierto
Descripción
Sumario:The use of artificial intelligence (AI) and machine learning (ML) is generating a significant transformation of the healthcare sector worldwide. These technologies are improving the efficiency of workflows, increasing the accuracy of diagnoses and raising the quality of patient treatment. However, they also pose complex regulatory challenges.This article examines the need for fundamental changes in the way AI and AA-based medical software is regulated, taking the role undertaken by the FDA. A literature review was conducted to analyze the current landscape of medical software using AI and AA and the implications it has on the use of these technologies. Key challenges in the regulation of AI and OA in the healthcare sector are highlighted, including the need for systemic approaches and the importance of flexibility and ongoing oversight in regulation. It is concluded that a systemic regulatory perspective, assessing healthcare ecosystems as a whole, should be considered to effectively address the challenges and complexities associated with these technologies in healthcare. This approach will also help build confidence and recognition of the transformative potential of AI and AA in healthcare.
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