期刊
ACADEMIC RADIOLOGY
卷 29, 期 3, 页码 409-412出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.acra.2020.12.017
关键词
Objectivity; Diagnostic imaging; Health history; Artificial intelligence; Deep learning imaging; Machine learning; Radiography; Bias
This research aims to trace the evolution of mechanical objectivity from empirical studies of early anatomists in the 19th century to modern advancements in medical imaging technology, while also highlighting the ongoing challenge of mitigating human bias despite technological progress.
Background: Before the advent of automatism in image-making practices, scientists, anatomists, and physicians artistically depicted simplified images for scientific atlas making. This technique conferred subjectivity to a supposedly objective scientific process, sparking confrontations between anatomists regarding accuracy that heralded a new concept in the late 19th century - mechanical objectivity that would revolutionize scientific knowledge and the field of medicine Objectives: The purpose of this health history research study is to trace the evolution of mechanical objectivity from empirical studies of early anatomists in the 19th century to the advent of x-ray technology, digitization of imaging, and disruptive technological innovations such as artificial intelligence, while simultaneously unveiling the challenges of mitigating human bias, despite advancements in medical imaging practices. Methods: This narrative literature review was conducted using the Scopus (R) database under the guidance of both medical historians and practicing physicians to ensure its applicability and historical accuracy Conclusion: Despite a century-long quest for optimizing mechanical objectivity in diagnostic imaging to more accurately and efficiently interpret medical images, human bias remains an important factor. This historical review describes the development of medical imaging technologies over the last century with emphasis on the role played by human bias and subjectivity in a rapidly expanding field of medical imaging technology including artificial intelligence.
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