Abstract
Artificial intelligence (AI) is a path-breaking advancement for many industries, including the health care sector. The expeditious development of information technology and data processing has led to the formation of recent tools known as artificial intelligence. Radiology has been a portal for medical technological advancements, and AI will likely be no dissimilar. Radiology is the platform for many technological advances in the medical field; AI can undoubtedly impact every step of a radiologist's workflow. AI can simplify every activity like ordering and scheduling, protocoling and acquisition, image interpretation, reporting, communication, and billing. AI has eminent potential to augment efficiency and accuracy throughout radiology, but it also possesses inherent drawbacks and biases.We collected studies that were published in the past five years using PubMed as our database. We chose studies that were relevant to artificial intelligence in radiology. We mainly focused on the overview of AI in radiology, components included in the functioning of AI, AI assisting in the radiologists' workflow, ethical aspects of AI, challenges, and biases that AI experiencing together with some clinical applications of AI. Of all 33 studies, we found 15 articles discussed the overview and components of AI, five articles about AI affecting radiologist’s workflow, five articles related to challenges and biases in AI, two articles discussed ethical aspects of AI, and six articles about practical implications of AI.We found out that the application of AI could make time-dependent tasks that can be performed effortlessly, permitting radiologists more time and opportunities to engage in patient care via increased time for consultation and development in imaging and extracting useful data from those images. AI could only be an aid to radiologists but will not replace a radiologist. Radiologists who use AI to their benefit, rather than to avoid it out of fear, might supersede those radiologists who do not. Substantial research should be done regarding the practical implications of AI algorithms for residents curriculum and the benefits of AI in radiology.
Highlights
BackgroundThe expeditious development of information technology and data processing has led to the formation of recent tools such as artificial intelligence (AI)
We mainly focused on the overview of Artificial intelligence (AI) in radiology, components included in the functioning of AI, AI assisting in the radiologists' workflow, ethical aspects of AI, challenges, and biases that AI experiencing together with some clinical applications of AI
We found out that the application of AI could make time-dependent tasks that can be performed effortlessly, permitting radiologists more time and opportunities to engage in patient care via increased time for consultation and development in imaging and extracting useful data from those images
Summary
BackgroundThe expeditious development of information technology and data processing has led to the formation of recent tools such as artificial intelligence (AI). AI application in radiology, machine learning (ML), has become a reality in clinical practice. AI has become an ambitious initiative in every facet of radiology [2]. Developments in both imaging and computers have synergistically promoted a fast ascent in the expected AI utilization in different radiological imaging tasks, such as risk assessment, identification, diagnosis, prognosis, therapy response, and risk of reoccurrence, as well as in multi-omics disease revelation [3]. Radiology varies from other image identification applications of AI algorithms. Radiomics is a compound multi-step process that helps clinical decision-making and prognosis prediction by integrating information from various tests involving clinical, molecular, imaging, and genomic data [5]. Some of the internal and external disadvantages in AI methods are impeding its implementation in the clinical area [2]
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