Analysis of Publication Activity and Research Trends in the Field of AI Medical Applications: Network Approach
Artificial intelligence (AI) has revolutionized numerous industries, including medicine. In recent years, the integration of AI into medical practices has shown great promise in enhancing the accuracy and efficiency of diagnosing diseases, predicting patient outcomes, and personalizing treatment pla...
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| Veröffentlicht in: | International journal of environmental research and public health 2023-03, Vol.20 (7), p.5335 |
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| creator | Karpov, Oleg E Pitsik, Elena N Kurkin, Semen A Maksimenko, Vladimir A Gusev, Alexander V Shusharina, Natali N Hramov, Alexander E |
| description | Artificial intelligence (AI) has revolutionized numerous industries, including medicine. In recent years, the integration of AI into medical practices has shown great promise in enhancing the accuracy and efficiency of diagnosing diseases, predicting patient outcomes, and personalizing treatment plans. This paper aims at the exploration of the AI-based medicine research using network approach and analysis of existing trends based on PubMed. Our findings are based on the results of PubMed search queries and analysis of the number of papers obtained by the different search queries. Our goal is to explore how are the AI-based methods used in healthcare research, which approaches and techniques are the most popular, and to discuss the potential reasoning behind the obtained results. Using analysis of the co-occurrence network constructed using VOSviewer software, we detected the main clusters of interest in AI-based healthcare research. Then, we proceeded with the thorough analysis of publication activity in various categories of medical AI research, including research on different AI-based methods applied to different types of medical data. We analyzed the results of query processing in the PubMed database over the past 5 years obtained via a specifically designed strategy for generating search queries based on the thorough selection of keywords from different categories of interest. We provide a comprehensive analysis of existing applications of AI-based methods to medical data of different modalities, including the context of various medical fields and specific diseases that carry the greatest danger to the human population. |
| doi_str_mv | 10.3390/ijerph20075335 |
| format | Article |
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Then, we proceeded with the thorough analysis of publication activity in various categories of medical AI research, including research on different AI-based methods applied to different types of medical data. We analyzed the results of query processing in the PubMed database over the past 5 years obtained via a specifically designed strategy for generating search queries based on the thorough selection of keywords from different categories of interest. 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| subjects | Algorithms Artificial Intelligence Big Data Biomedical Research Clinical trials Computer industry Coronaviruses COVID-19 Deep learning Fuzzy sets Health care Health Services Research Human populations Humans Keywords Machine learning Medical equipment Medical imaging equipment Medical research Medical technology Medicine Medicine, Experimental Methods Patients Physicians Practice Queries R&D Research & development Searching Software Task analysis Technology Trends |
| title | Analysis of Publication Activity and Research Trends in the Field of AI Medical Applications: Network Approach |
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