• MR.M JANAKI RAMUDU
• P M J NEHA
• M KISHORE KARTHIKEYA
• P CHANDRA KIRAN
• D NAVEEN KUMAR

Alzheimer’s Disease (AD) is a progressive condition that affects memory, thinking, and daily life. Early detection is crucial in managing symptoms and slowing progression. Our machine learning-based prediction system helps assess Alzheimer’s risk using health and lifestyle factors such as age, medical history, and cognitive function. We use Random Forest and Gradient Boosting, ensuring reliable predictions. The system processes data efficiently, handling missing values and imbalanced datasets for improved performance. With a Flask-powered web interface, users can input their details and receive a quick risk assessment. The platform also includes data visualization tools, making results easy to understand. While not a replacement for clinical diagnosis, this AI-driven tool empowers individuals and healthcare professionals to take proactive steps toward early intervention and better brain health.

Alzheimer’s disease, machine learning, early diagnosis, Flask-powered web interface, Random Forest, Gradient Boosting, data preprocessing, healthcare analytics, risk assessment.

"PRELIMINARY WARNING SYSTEM FOR ALZHEIMER'S DISEASE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.d963-d970, March-2025, Available :http://www.jetir.org/papers/JETIR2503409.pdf

"PRELIMINARY WARNING SYSTEM FOR ALZHEIMER'S DISEASE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppd963-d970, March-2025, Available at : http://www.jetir.org/papers/JETIR2503409.pdf