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The purpose of this paper is to detect Alzheimer’s Disease using Deep Learning and Machine Learning algorithms on the early basis which is being further optimized using CSA(Crow Search Algorithm). Alzheimer’s is one of kind and fatal. The early detection of Alzheimer’s Disease because of it’s progressive risk and patients all around the world. Early detection of AD is promising as it can help lot of patients to predetermine the condition they may face in future. AD being progressive, can be prevented if detected early. On worse stage, the curing of this disease is very difficult and expensive. So, by analyzing the consequences of AD, we can make use of Artificial intelligence technology by using MRI scanned images to classify the patients if they may or may not have AD in future. Using of Bio-inspired algorithm can maximize the result and accuracy for this purpose. After comparing the results of the various AI technologies, CSA came to be the best approach, using it with ML algorithms.

Jupyter Notebook 99.33% Python 0.67%
alzheimers-disease crow-search-algorithm deep-neural-networks image-classification

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Hello, I need some help.
What format should resize.ipynb and resize data.ipynb read in?
What should I do with the data if I'm going to run train.py?
Thank you first!

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