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@article{163397,
        author = {Leena Supe and Manasvi Tayde and Sumit Patil and Divya Chaudhari and Dhanashree S. Tayade},
        title = {PARALYSIS AGITANS DISEASE DETECTION USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {11},
        pages = {912-917},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=163397},
        abstract = {In this new technological cycle, current challenges demand a profound re-orientation of a global healthcare system. A more efficient system is required to cope with increased life expectancy which is associated with a prevalence of chronic neurological disorders such as Paralysis Agitans. The Paralysis Agitans disease is a neurodegenerative disorder affecting 60 percent of people. At this moment there is no such system available to detect the Paralysis Agitans disease with good accuracy. The detection of Paralysis Agitans disease is based on medical history, symptoms, and the neurological and physical Exam. The proposed system is used to detect Paralysis Agitans disease with the help of various machine learning techniques. The Paralysis Agitans detection system will achieve good results.},
        keywords = {Algorithms, Handwriting analysis, Machine Learning, paralysis Agitans(PA) disease or Parkinson's Disease(PD).},
        month = {},
        }