Análisis de Modelos de Inteligencia Artificial Aplicados a Sistemas Biomédicos e Internet de Objetos Médicos

Abstract

This article addresses the comparison of artificial intelligence algorithms applied to biomedical systems, with a specific focus on patients with chronic diseases. The goal is to identify advantages, disadvantages, and suggest improvements for these algorithms, emphasizing the relevance of medical devices and the Internet of Medical Things (IoMT) to enhance the diagnosis and quality of life for patients. The study aims to analyze the parameters of AI algorithms applied to biomedical devices, identify areas for improvement, and select the most efficient algorithm. Additionally, it seeks to evaluate the impact of AI use in biomedical devices from the user's perspective. The research employs a mixed- methods approach, combining exploratory research with a mixed focus to analyze theoretical information applied to biomedical systems. Two surveys on the comfort and accuracy of medical devices are implemented, along with interviews with specialist doctors. Data collection is carried out in a mixed manner, combining quantitative and qualitative methods. A systematic literature review on artificial intelligence algorithms and IoMT is conducted. Simultaneously, a structured survey is administered to patients to assess the effectiveness of algorithms in medical devices, and semi-structured interviews are conducted with specialist doctors to obtain qualitative perspectives. The data analysis is divided into several phases, identifying relevant resources from the literature, and evaluating the performance of medical devices. The second phase conducts a comparative analysis of algorithms. The results are statistically analyzed using Excel functions, including averages and data tabulation, with effective visualization through graphs and pivot tables. This methodological approach provides a comprehensive understanding of artificial intelligence algorithms applied to medical systems, highlighting their applicability in the context of chronic diseases, and promoting significant improvements in patient care and quality of life. This study aims to contribute to knowledge in the field of AI applied to health, in the context of biomedical systems and IoMT, with the goal of improving effectiveness and efficiency in managing critical medical conditions such as diabetes and hypertension.