REVIEW PAPER
Applications of Artificial Intelligence (AI) in medicine
1
Uniwersytet Medyczny w Lublinie, Polska
Med Og Nauk Zdr. 2021;27(3):213-219
KEYWORDS
TOPICS
ABSTRACT
Introduction and objective:
Artificial intelligence is a relatively new field of medical sciences. Its application in medicine is described in regularly appearing publications, which often focus on the use of deep learning algorithms based on neural networks that are capable of recognizing pathological changes in images. The aim of this study is to discuss possibilities of application of artificial intelligence in medicine, particularly radiology and pathomorphology, and to present the results achieved.
Review methods:
Databases of Medline (PubMed) and Google Scholar were searched using keywords: ‘artificial intelligence’, ‘deep learning’, ‘machine learning’, ‘digital pathology’, and ‘convolutional neural network’. The search was undertaken in March 2021. Studies published in English during 2015–2021 were selected.
Brief description of the state of knowledge:
There are many reports concerning the use of artificial intelligence in various fields of medicine, such as radiology and pathomorphology. Multiple research shows that self-learning algorithms are capable of finding pathologies in radiograms, computed tomography scans, or microscopic slides with accuracy equal to or even better than physicians. The study indicates significant advantages resulting from synergic cooperation of artificial intelligence and physicians.
Summary:
Results achieved by artificial intelligence based algorithms provide evidence for improvement of patient diagnosis, predominantly by supplementation of physicians’ knowledge and experience. It is also an important fact that the use of AI decreases the risk of medical error, e.g. failure to recognize a pathological change visible on RTG.
Artificial intelligence is a relatively new field of medical sciences. Its application in medicine is described in regularly appearing publications, which often focus on the use of deep learning algorithms based on neural networks that are capable of recognizing pathological changes in images. The aim of this study is to discuss possibilities of application of artificial intelligence in medicine, particularly radiology and pathomorphology, and to present the results achieved.
Review methods:
Databases of Medline (PubMed) and Google Scholar were searched using keywords: ‘artificial intelligence’, ‘deep learning’, ‘machine learning’, ‘digital pathology’, and ‘convolutional neural network’. The search was undertaken in March 2021. Studies published in English during 2015–2021 were selected.
Brief description of the state of knowledge:
There are many reports concerning the use of artificial intelligence in various fields of medicine, such as radiology and pathomorphology. Multiple research shows that self-learning algorithms are capable of finding pathologies in radiograms, computed tomography scans, or microscopic slides with accuracy equal to or even better than physicians. The study indicates significant advantages resulting from synergic cooperation of artificial intelligence and physicians.
Summary:
Results achieved by artificial intelligence based algorithms provide evidence for improvement of patient diagnosis, predominantly by supplementation of physicians’ knowledge and experience. It is also an important fact that the use of AI decreases the risk of medical error, e.g. failure to recognize a pathological change visible on RTG.
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| eISSN: | 2084-4905 |
| ISSN: | 2083-4543 |
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