A Review of Artificial Intelligence Application in Healthcare Sectors
Keywords:
Artificial Intelligence, large language models, healthcare systems, multimodal models, agentic clinical workflowsAbstract
Artificial Intelligence (AI) is no longer an experimental method for computation, but has become a game-changer in the present day medical field. In the past decade, machine learning (ML), deep learning (DL), and now large language models (LLMs) have found their way into most medical specialties, ranging from radiology and oncology to cardiology, neurology, and hepatology. A literature review was conducted to collate peer-reviewed research articles, published from 2020 to 2025, on the evolution, application fields, methodological trends, ethical issues, and unanswered questions about the use of AI in medicine. Using more than hundred primary studies and umbrella reviews, the review reveals that the primary data sources are diagnostic imaging, electronic health records (EHRs), and biomarker analytics, with the rapid growth of multimodal foundation models and agentic clinical workflows emerging in the landscape.
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