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Ethical Data Collection for Medical Image Analysis: a Structured Approach

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 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asian Bioethics Review Springer Journals

Ethical Data Collection for Medical Image Analysis: a Structured Approach

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References (39)

Publisher
Springer Journals
Copyright
Copyright © National University of Singapore and Springer Nature Singapore Pte Ltd. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
ISSN
1793-8759
eISSN
1793-9453
DOI
10.1007/s41649-023-00250-9
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Asian Bioethics ReviewSpringer Journals

Published: Jan 1, 2024

Keywords: Data ethics; Medical imaging; Data collection; Data science; Research ethics; Data privacy; Data analytics

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