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@article{205038,
        author = {Gagan kumar and Syed Md Salman and Dr.Neha kumari},
        title = {Intelligent Referral and Healthcare Resource Recommendation System with AI Assistance},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {5706-5713},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205038},
        abstract = {The Increasing Challenges in Modern Healthcare delivery has posed challenges to the referral process management and optimization of healthcare resources. Patients often find it difficult to pinpoint apt hospitals regarding their needs, accessibility, and service suitability, whereas healthcare a lack of common decision-support tools for a proper patient distribution. Such problems are especially exacerbated by lack of access to real-time institutional healthcare data because of privacy and regulatory issues. This study offers an Intelligent Referral and Healthcare Resource Recommendation System with AI Assistance developed in order to support informed decision-making in the field of healthcare using publicly accessible information. In this research paper, we are going to propose the Intelligent Referral Resource Recommendation System for the healthcare sector facilitated by the use of AI assistance to make the right healthcare decisions based on publicly available information. Our system will comprise location-based referral of hospitals with conversational symptom-reporting assistant, which collects symptom-relate no specific guidance, but provides recommendations for referral. To low severity conditions, basic medicine recommendations amp; precautions. recommendations are given, and individuals in more at-risk groups are advised towards appropriate health facilities. It will be capable of operating from a system for it to be useful. It operates in both online and offline modes. It uses third-party services in online mode to fetch the latest information from external APIs and open data platforms. This is in relation to the hospital location and accessibility. For the offline mode, the It uses the hospital dataset, which is organized and kept in an organized manner at the local level basically. It takes into account the overall environment, and I needed to learn Offers suggestions related to nearby hospitals and categories. Recommendation process is a hybrid methodology incorporating a wide range of quantitative criteria. Incorporates the findings from location analysis and rule-based prioritization and artificially intelligent decision-aides: An empirical test verifies that when very similar cases are presented that is, the time searching for a hospital is reduced by User decision making. In conclusion, the software provides scalable solution, Privacy-friendly solution, Connectivity-Aware Solution for intelligent referral and healthcare resource recommendation. Future studies might examine a range of community sourced indicators, optimizing patient prioritization, and genuine verification of the system in real world situations if possible.},
        keywords = {},
        month = {June},
        }