Secured medical document extraction in E-Health Care system using data mining techniques
With the growing digitization of healthcare data, the need for efficient and secure extraction of valuable information from medical documents has become paramount. This study focuses on the development of a robust E-Health Care system that employs advanced data mining techniques to extract relevant medical information from diverse and often unstructured datasets. The primary objective is to enhance the accuracy and speed of document processing while ensuring the security and confidentiality of sensitive patient information.The proposed system utilizes state-of-the-art data mining algorithms to analyze electronic medical records, diagnostic reports, and other healthcare documents. Through the integration of natural language processing and machine learning techniques, the system aims to intelligently extract key medical information such as patient demographics, diagnosis codes, treatment plans, and medication details. Moreover, the implementation of encryption and access control mechanisms ensures the safeguarding of patient privacy and compliance with regulatory standards.
The research also addresses challenges associated with the variability and complexity of medical documents by employing feature engineering and document normalization techniques. Additionally, a comprehensive evaluation of the system’s performance is conducted, considering factors such as extraction accuracy, processing speed, and security robustness.
