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@article{185605,
        author = {R Jyosna devi and Dr.Sadish Sendhil Murugaraj},
        title = {LUNG CARE-OPT: A NOVEL OPTIMIZATION FRAMEWORK BUILT TO HANDLE DIVERSE PATIENT DATA},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {2124-2131},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185605},
        abstract = {Lung cancer remains the leading cause of cancer deaths worldwide, a reality largely driven by late detection and unreliable prognoses. To address these challenges, our research introduces Lung Care-Opt, a novel optimization framework built to handle diverse patient data. This system integrates clinical notes, medical imaging, and biomarker information, leveraging machine learning combined with metaheuristic methods for smarter feature selection and tuning. Unlike conventional models, LungCare-Opt is designed to perform two critical jobs simultaneously: diagnosing the disease and predicting long-term survival. We prioritized making the system understandable, efficient, and genuinely useful in a clinical setting. Our experimental results are promising, showing that the model delivers higher precision, a significant reduction in false positives, and more accurate patient outcome predictions. We believe this framework represents a practical and scalable step forward in the fight against lung cancer.},
        keywords = {Lung cancer, early diagnosis, prognosis, optimization algorithms, machine learning, clinical decision support.},
        month = {October},
        }