A MODERN RENAISSANCE OR AN ETHICAL CONUNDRUM: REVIEWING THE IMPLICATIONS OF ARTIFICIAL INTELLIGENCE IN THE FIELD OF RADIOLOGY
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Review
P: 8-12
February 2021

A MODERN RENAISSANCE OR AN ETHICAL CONUNDRUM: REVIEWING THE IMPLICATIONS OF ARTIFICIAL INTELLIGENCE IN THE FIELD OF RADIOLOGY

Turk Med Stud J 2021;8(1):8-12
1. Services Institute of Medical Sciences, Lahore, PAKISTAN
2. Allama Iqbal Medical College, Lahore, PAKISTAN
No information available.
No information available.
Received Date: 11.01.2021
Accepted Date: 25.01.2021
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ABSTRACT

Recent progress in the field of artificial intelligence has found its way into the diverse realms of medical imaging and radiology, raising questions regarding its potential, efficiency, accuracy, and reliability. This review aims to educate radiologists and medical students regarding the uncharted world of artificial intelligence through the discussion of its achievements in radiology while keeping an ethical and prognostic outlook in mind. Artificial intelligence, through the application of its subsets (i.e. machine learning and deep learning), has caused vast expansions in radiology, such as automating diagnoses. Pneumonia, pneumothorax, pulmonary tuberculosis, pulmonary nodules, etc. can now be detected through the use of various artificial intelligence algorithms. However, the acceptability of these highly accurate systems is still a matter of massive doubt. Educating the healthcare professionals in this regard would alleviate the fear of an unknown computing system while also answering numerous misconceptions. Moreover, with acceptability comes a huge moral and ethical responsibility. Ethical codes need to be devised that provide appropriate solutions to the moral problems connected with artificial intelligence. Thus, with all of these factors under consideration, artificial intelligence has enormous potential in the field of radiology and will broaden the horizon of healthcare professionals by creating a greater number of computing-related opportunities.

Keywords: Artificial intelligence, radiology, ethics, deep learning, machine learning

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