Achievements and prospects for the application of artificial intelligence technologies in medicine: an overview. Part 1
| Autor: | Vitaly A. Berdutin, Olga P. Abaeva, Tatyana E. Romanova, Sergey V. Romanov |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Sociology of Medicine. 21:83-96 |
| ISSN: | 2413-2942 1728-2810 |
| DOI: | 10.17816/socm106054 |
| Popis: | On a global scale, a radical transformation of the healthcare sector is taking place right before our eyes. Health care systems in many countries are changing at an incredible pace under the pressure of innovative digital platforms that have gained popularity under the names of artificial intelligence (AI) and machine learning (ML). AI systems, powered by massive amounts of data collected from everywhere, are able to guarantee optimal decision making for key players in the healthcare industry, from the pharmaceutical industry to the smallest healthcare providers. This article presents the results of the analysis of achievements and prospects for the use of innovative digital technologies and platforms in modern health care. According to international experts in medicine, it is possible to automate 36% of functions, primarily at the levels of data collection and analysis, and the use of AI technologies can significantly increase the gross profit of firms and organizations in relation to medical activities. There is no doubt about this since information has already become the main driver of management across all sectors of the global economy in general and in the health care sector in particular. The main motivations for the penetration of AI into health care are the escalating costs and the urgent need to limit them, the problem of poor-quality diagnostics (up to 30% of ongoing studies turn out to be unreliable or are misinterpreted) and the desire for standardization and automation of routine functions up to the creation of self-managed diagnostic models. However, the biggest challenge for AI in healthcare is not whether these technologies will be useful enough, but how to ensure that they are quickly and efficiently implemented in everyday clinical practice. |
| Databáze: | OpenAIRE |
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