• Pranali Rakshe
• Krushna Dhole
• Aditi Kokil
• Priya Medankar
• Prof K.S. Warke

Alzheimer's disease is a progressive and neurodegenerative disorder which involves multiple molecular mechanisms. One of the most common signs of Alzheimer’s disease, especially in the early stage, is forgetting recently learned information. Intense research during the last years has accumulated a large body of data and the search for sensitive and specific biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and the current tests do not accurately detect the process leading to neuro-degeneration. Motivated by this, we thought of developing a system that detects the disease at early stage. To achieve this we are considering patient’s daily routine and his personal details. The system will have a questionnaire and each answer will have a certain weightage. To calculate the final prediction we will use classification algorithm as SVM and Naive Bayes algorithm. The predicted result will be final percent prediction. Depending on this percent, doctor recommendation will be suggested by the system.

"PREDICT THE ALZHEIMER’S DISEASE BASED ON MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.645-648, May-2019, Available :http://www.jetir.org/papers/JETIR1905295.pdf

"PREDICT THE ALZHEIMER’S DISEASE BASED ON MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp645-648, May-2019, Available at : http://www.jetir.org/papers/JETIR1905295.pdf