Аrtificial intelligence in healthcare: managerial and clinical perspective

Abstract

Relevance . The modern healthcare system is entering a stage of deep digital transformation, with artificial intelligence becoming a key tool. The development of algorithms, the growth of computing power and the accumulation of large amounts of medical information have made it possible to move from theoretical models to real digital solutions in clinical and management practice. From a managerial point of view, artificial intelligence opens up new opportunities for analyzing big data, predicting the needs of the population for medical care, optimizing patient routing and resource allocation. The use of intelligent analytical platforms helps to increase the efficiency of medical organizations, reduce the administrative burden and implement the principles of quality management. From a clinical perspective, artificial intelligence is becoming a tool for improving the accuracy of diagnosis, early detection of diseases, personalization of treatment and evaluation of the effectiveness of therapy. Machine learning algorithms are actively used in radiology, cardiology, oncology and telemedicine, providing an additional level of expert support to the doctor and reducing the likelihood of diagnostic errors. Special attention is paid to issues of ethics, clinical verification of results, protection of personal data and preservation of the leading role of the doctor as a responsible decision-making subject. The article examines the organizational, professional and socio-cultural aspects of the use of artificial intelligence in healthcare in the Republic of Uzbekistan. The purpose of the study : to summarize modern approaches to the use of artificial intelligence in healthcare, evaluate the clinical and managerial possibilities of its use, identify limitations and ethical aspects. Materials and methods . An analytical review of international publications (WHO, NEJM, JAMA, Nature Medicine, and others), as well as regulatory documents on digital healthcare, was conducted. A descriptive and analytical method was used to summarize data on clinical and managerial applications of artificial intelligence. Results . The use of artificial intelligence is highly effective in the following areas: medical image analysis (computer and magnetic resonance imaging, X-ray); disease prediction (cardiovascular, oncological, endocrine); clinical decision support; monitoring of chronic patients; patient flow management; optimization of healthcare resources. In a management context, artificial intelligence makes it possible to analyze large amounts of data, predict the burden on the healthcare system, and increase the efficiency of resource allocation. Despite its high productivity, its implementation is accompanied by a number of limitations. The main problems are the quality of the source data, the risk of algorithmic errors, and limited interpretability of the models. Ethical issues are of particular importance: the protection of personal data, the transparency of algorithms and the preservation of the role of the doctor as a subject of decision-making. Artificial intelligence does not replace clinical thinking, but acts as a tool to enhance it. Thus, a new healthcare model based on the use of digital technologies is being formed. Conclusion . Artificial intelligence is an important tool for healthcare transformation, improving the quality of medical care and management efficiency. Its application requires the development of digital infrastructure, the training of medical personnel and the formation of a new ethical and legal model.