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Showing 2 results for Artificial Intelligence

Monireh Rahimkhani, Maryam Gilani,
Volume 20, Issue 1 (6-2024)
Abstract

Antibiotic resistance has increased significantly in recent years. On the other hand, machine learning (ML) algorithms are increasingly used in medical research and healthcare and are gradually improving clinical performance.
Using ML to fight antimicrobial resistance (AMR) is one of the most critical areas of interest among the various applications of these new methods. The rise of antibiotic resistance and managing multidrug-resistant infections that are difficult to treat are important challenges.
Both supervised and unsupervised machine learning tools have been successfully used to predict early antibiotic resistance and thus support clinicians in selecting the appropriate treatment. Machine learning and artificial intelligence (AI) in predicting antimicrobial resistance are among today's sciences. Therefore, an antimicrobial stewardship program (ASP) should be implemented to optimize antibiotic prescribing and limit AMR.

Manoochehr Karami,
Volume 20, Issue 3 (12-2024)
Abstract

Artificial intelligence (AI) refers to the process in which computers, rather than human intelligence, perform tasks, such as early warning of an epidemic. This editorial aimed to describe the potential applications of digital health and the challenges faced by the health system of Iran concerning the application of artificial intelligence and innovative technology in public health surveillance and early warning of epidemics. The use of new technologies at national and subnational levels for early warning of public health threats requires a suitable platform within the context of disease surveillance systems. The Iran health system currently utilizes a syndromic approach and event-based surveillance to monitor acute respiratory infections. However, the structure of Iran's national communicable disease surveillance system has faced challenges due to the inability to share and exchange data at the level of primary health care data sources. Accordingly, application and integration of AI should be considered as Iran’s health priority to promote infrastructure and technology requirements, including compatibility, interoperability, and strategies for ethical and responsible use by public health authorities. Since pandemics and epidemics have not been limited to the previous ones, such as COVID-19, influenza, SARS, dengue fever, and similar threats, operations planning is required for the integration of artificial intelligence tools to prepare and respond to biological threats promptly by the Iranian Ministry of Health, stakeholders, and other parties.


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