We use several techniques in medical document processing including optical character recognition (OCR), natural language processing (NLP), and machine learning. OCR involves the conversion of scanned documents into machine-readable text, which can then be analyzed by NLP algorithms to extract useful information. NLP techniques involve the analysis of natural language text to identify relevant information, such as patient demographics, diagnoses and treatments. Machine learning algorithms can be trained to automatically classify and extract information from medical documents, improving accuracy and efficiency.

Medical document processing has many potential benefits, including improving the accuracy of diagnoses, reducing the time required to make treatment decisions and increasing the efficiency of healthcare providers. It also has the potential to reduce costs associated with healthcare by streamlining administrative processes and reducing the need for manual data entry and document handling.