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@article{209088,
        author = {Nagashree Baggon and Niharika Shambhu Gouda and Prakrathi Shetty and Suchitra M and Miss Amulya},
        title = {Medical Report Interpretation Using NLP},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {5},
        pages = {517-524},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=209088},
        abstract = {Medical report contain valuable clinical informa¬tion in unstructured and semi-structured text, making man¬ual interpretation time consuming for patient and health¬care professionals. This paper presents a Natural Language Processing (NLP) based system for medical report based on multiple disease and medical conditions. This system ac¬cepts medical documents such as PDF, DOCX, and TXT files and processes them using text processing, clinical entity extraction, terminology normalization, and contextual analysis. The system identify important medical data means symptoms, diseases, medications, investigations, procedures, and clinical findings. The extracted data is converted into semantic represen¬tation with patient-friendly explanations. In addition, a doctor-oriented research module allows authorized healthcare profession-als to search and review symptoms and related clinical data while maintaining privacy and responsible use of clinical data. The system is intended as an information and clinical decision-support tool rather than an autonomous diagnostic system},
        keywords = {Natural Language Processing, Medical Report Interpretation, Clinical information Extraction, Named Entity Recognition, Clinical NLP, Medical Text Mining, Clinical Decision Support.},
        month = {October},
        }