The integration of computer vision (CV) techniques in healthcare has revolutionized the analysis of medical data, enabling improved diagnostics, treatment planning, and patient care. However, the application of Computer vision methods to analyze financial information within healthcare systems remains an underexplored area. This survey paper provides a comprehensive review of computer vision methodologies applied to financial data analysis in healthcare, focusing on tasks such as invoice processing, expense tracking, fraud detection, and cost optimization. We explore the intersection of Computer vision and financial informatics, highlighting key algorithms, datasets, and challenges. Additionally, we discuss the potential of these methods to enhance financial transparency, reduce operational costs, and improve resource allocation in healthcare systems. This paper aims to serve as a foundational resource for researchers and practitioners working at the intersection of computer vision, healthcare, and financial analytics.
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