The Role of Artificial Intelligence in Diagnostic Decision-Making: A Review of Current Evidence
Keywords:
Artificial Intelligence, diagnostic decision-making, machine learning, deep learning, radiology, clinical decision support, healthcare, AI applicationsAbstract
Artificial Intelligence (AI) has revolutionized diagnostic decision-making in healthcare, offering powerful tools for improving the accuracy, efficiency, and speed of diagnoses across various medical domains. Machine learning algorithms, deep learning techniques, and natural language processing have shown great promise in supporting clinicians with data-driven decisions. This review explores current evidence on the role of AI in diagnostic decision-making, highlighting its applications, challenges, and future potential. AI-powered diagnostic tools have demonstrated effectiveness in fields such as radiology, pathology, cardiology, and dermatology, where they assist in image analysis, disease prediction, and clinical decision support. However, issues related to data quality, algorithmic bias, and integration into clinical workflows remains significant barriers. The article concludes by emphasizing the need for continued innovation, regulatory frameworks, and interdisciplinary collaboration to maximize the benefits of AI in healthcare diagnostics.
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Copyright (c) 2025 Ayesha Khan, Muhammad Ali, Sana Riaz
This work is licensed under a Creative Commons Attribution 4.0 International License.
