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@article{188415,
        author = {Vedant Mahesh Tumme and Srushti Velhal and Vihaan Nair and Ajinkya Vyavahare and Pranjali Vyavahare},
        title = {AI-Driven Prediction and Management of Hospital Resources for Enhanced Healthcare Efficiency},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {2780-2786},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188415},
        abstract = {The hospital resources like the intensive care unit beds, ventilators, oxygen and the staff may occasionally prove a burden to the hospital especially in cases of emergency or when the number of patients admitted to the hospital takes an unexpected turn. The strategies of planning that are based on old-fashioned manual techniques and past historical averages cannot be compatible with the unpredictable and dynamic character of healthcare. This paper presents hospital resource forecasting (AI-based) technology, which utilizes machine learning and predictive analytics to offer both short-term and long-term predictions of resource requirements in the healthcare setting. Our forecasting system comes up with the right forecasts based on patient admission trend data, lagging medical records data, seasonal trends and real time inputs of hospital data. The forecasting user interface has an interactive dashboard, which is used to aid pre-emptive decision making when allocating resources to the hospital. Our forecast technology presents healthcare delivery and ultimately patient outcome improvements, in the form of preparedness, reduction in down-time, and efficiency.},
        keywords = {Artificial Intelligence, Predictive Analytics, Hospital Resource Management, Healthcare Informatics, ICU Bed Prediction, Medical Resource Allocation.},
        month = {December},
        }