Diagnostic Imaging and Mechanical Objectivity in Medicine.
Artificial intelligence
Bias
Deep learning imaging
Diagnostic imaging
Health history
Machine learning
Objectivity
Radiography
Journal
Academic radiology
ISSN: 1878-4046
Titre abrégé: Acad Radiol
Pays: United States
ID NLM: 9440159
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
received:
09
11
2020
revised:
29
12
2020
accepted:
31
12
2020
pubmed:
25
1
2021
medline:
11
3
2022
entrez:
24
1
2021
Statut:
ppublish
Résumé
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 19 This narrative literature review was conducted using the Scopus® 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.
Sections du résumé
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 19
METHODS
This narrative literature review was conducted using the Scopus® 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.
Identifiants
pubmed: 33485774
pii: S1076-6332(21)00002-7
doi: 10.1016/j.acra.2020.12.017
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
409-412Informations de copyright
Copyright © 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.