AI-Driven OCR for Comprehensive Medical Label Interpretation
Aditya Kushwaha, Pranjal Prasad, Aarna Singh, Tanu Sharma, Vaishali Deshwal · 2025
This paper presents a comprehensive analysis of Optical Character Recognition (OCR) technology and its relevance to the healthcare industry with a specific emphasis on recognition of medical tags and texts. OCR technology considerably facilitates the process of transforming paper- based patient records into digital systems, thereby solving the problems of data storage, accuracy as well as reducing the possibility of arbitrary mistakes. The review offers insights on OCR, featuring its components and how they operate starting from the image acquisition as well as the post processing and assesses the significance of such technology to the health service providers. This is because the solution is compatible with artificial intelligence and machine learning technologies and therefore can cope with a variety of medical records. Some applications demonstrate how OCR helps to reduce efforts in the analysis of cancer from pathology reports as well as protect patients' private information within medical pictures. Even with these existing opportunities, there are still problems concerning accurate analysis of information with many intricate structures. This paper examines how OCR might advance in future prospects, with an emphasis on the adoption of clinical practices and frameworks, and data safety's ethical aspects.