APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN MEDICAL DIAGNOSIS AND ITS IMPLICATIONS FOR DIAGNOSTIC ACCURACY, CLINICAL PRACTICE, AND PATIENT SAFETY
DOI:
https://doi.org/10.56238/levv17n60-022Keywords:
Artificial Intelligence, Computer-Assisted Diagnosis, Patient Safety, Clinical Decision Making, Sensitivity and SpecificityAbstract
Considering the progressive advancement of digital technologies in healthcare and the need to increase diagnostic accuracy and patient safety, it becomes relevant to understand the impacts of artificial intelligence on medical diagnosis and its repercussions on contemporary clinical practice. This study aims to analyze the applications of artificial intelligence in medical diagnosis and its implications for diagnostic accuracy, clinical practice, and patient safety. To this end, an integrative literature review with a qualitative approach was conducted using the PubMed/MEDLINE, SciELO, Virtual Health Library, and Scopus databases, using the descriptors provided. Studies with clinical validation and relevance to clinical practice were included. Thus, it was observed that artificial intelligence demonstrated a high capacity for interpreting imaging exams, optimizing care flows, supporting clinical decision-making, and reducing diagnostic errors, especially in areas such as radiology, oncology, and digital pathology. However, challenges persist related to algorithmic transparency, diagnostic biases, clinical safety, and structural limitations for large-scale implementation. It is concluded that artificial intelligence has significant potential to strengthen the diagnostic quality and efficiency of health services, although its incorporation requires continuous validation, ethical regulation, and responsible integration into medical practice.
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