ARTIFICIAL INTELLIGENCE IN EARLY DIAGNOSIS OF CHRONIC DISEASES: CHALLENGES AND PERSPECTIVES

Abstract

Early diagnosis of chronic diseases is essential to reduce morbidity and mortality and costs associated with treatment. Artificial intelligence (AI) has emerged as a promising tool in this context, by offering predictive models and algorithms capable of analyzing large volumes of data quickly and accurately. This study aimed to identify and discuss the main challenges and perspectives related to the application of AI in the early diagnosis of chronic diseases. An integrative literature review was conducted in relevant databases, focusing on articles published between 2018 and 2023. The results pointed to significant advances in the ability of AI to integrate heterogeneous data, such as medical images and clinical information, favoring more accurate diagnoses. However, limitations related to data quality, algorithmic bias, and ethical and regulatory challenges still represent barriers to large-scale implementation. It is concluded that, although AI has a transformative potential in the diagnosis of chronic diseases, its effective application requires multidisciplinary approaches, investments in technological infrastructure, and the creation of robust regulations that guarantee safety and efficacy.