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Ethical Data Collection for Medical Image Analysis: a Structured Approach

Due to advancements in technology such as data science and artificial intelligence, healthcare research has gained momentum and is generating new findings and predictions on abnormalities leading to the diagnosis of diseases or disorders in human beings. On one hand, the extensive application of dat...

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Detalles Bibliográficos
Autores principales: Padmapriya, S. T., Parthasarathy, Sudhaman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10088772/
https://www.ncbi.nlm.nih.gov/pubmed/37361687
http://dx.doi.org/10.1007/s41649-023-00250-9
Descripción
Sumario:Due to advancements in technology such as data science and artificial intelligence, healthcare research has gained momentum and is generating new findings and predictions on abnormalities leading to the diagnosis of diseases or disorders in human beings. On one hand, the extensive application of data science to healthcare research is progressing faster, while on the other hand, the ethical concerns and adjoining risks and legal hurdles those data scientists may face in the future slow down the progression of healthcare research. Simply put, the application of data science to ethically guided healthcare research appears to be a dream come true. Hence, in this paper, we discuss the current practices, challenges, and limitations of the data collection process during medical image analysis (MIA) conducted as part of healthcare research and propose an ethical data collection framework to guide data scientists to address the possible ethical concerns before commencing data analytics over a medical dataset.