عنوان انگلیسی مقاله:
Strengths, Weaknesses, Opportunities, and Threats Analysis of Artificial Intelligence and Machine Learning Applications in Radiology
ترجمه فارسی عنوان مقاله:
نقاط قوت ، ضعف ، فرصت و تحلیل تهدیدات هوش مصنوعی و برنامه های یادگیری ماشین در رادیولوژی
Sciencedirect - Elsevier - Journal of the American College of Radiology, 16 (2019) 1239-1247: doi:10:1016/j:jacr:2019:05:047
Teodoro Martín Noguerol, MDa, Félix Paulano-Godino, PhDb, María Teresa Martín-Valdivia, PhDc, Christine O. Menias, MDd, Antonio Luna, MD, PhDa
Currently, the use of artificial intelligence (AI) in radiology, particularly machine learning (ML), has become a reality in clinical practice.
Since the end of the last century, several ML algorithms have been introduced for a wide range of common imaging tasks, not only for
diagnostic purposes but also for image acquisition and postprocessing. AI is now recognized to be a driving initiative in every aspect of
radiology. There is growing evidence of the advantages of AI in radiology creating seamless imaging workflows for radiologists or even
replacing radiologists. Most of the current AI methods have some internal and external disadvantages that are impeding their ultimate
implementation in the clinical arena. As such, AI can be considered a portion of a business trying to be introduced in the health care
market. For this reason, this review analyzes the current status of AI, and specifically ML, applied to radiology from the scope of
strengths, weaknesses, opportunities, and threats (SWOT) analysis.
Key Words: Artificial intelligence | deep learning | machine learning | opportunity | radiomics | strength | threat | weakness