{"id":46817,"date":"2024-11-15T00:00:00","date_gmt":"2024-11-15T08:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/blog\/exploring-alzheimers-cognitive-decline-and-mental-distress-through-the-lens-of-griddb\/"},"modified":"2025-11-13T12:57:08","modified_gmt":"2025-11-13T20:57:08","slug":"exploring-alzheimers-cognitive-decline-and-mental-distress-through-the-lens-of-griddb","status":"publish","type":"post","link":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/en\/blog\/exploring-alzheimers-cognitive-decline-and-mental-distress-through-the-lens-of-griddb\/","title":{"rendered":"Exploring Alzheimer’s Cognitive Decline and Mental Distress through the Lens of GridDB"},"content":{"rendered":"
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Exploring Alzheimer's: Cognitive Decline and Mental Distress through the Lens of GridDB\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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A progressive brain disorder, Alzheimer's disease often leads to the degeneration of brain cells. It is the most common cause of dementia, characterized by memory loss, cognitive decline, and behavioral changes. Being a brain disorder, Alzheimer's disease gradually impairs one's ability to perform daily activities. If you\u2019ve watched the award-winning movie 'Still Alice', you will know how deep is the personal impact of Alzheimer's disease. While risk factors of Alzheimer's include age, genetics, and lifestyle choices, it is crucial to delve deeper to understand and manage the symptoms effectively.<\/p>\n

In this article, we will perform a comprehensive analysis of Alzheimer's risk factors using GridDB and Python. By leveraging GridDB\u2019s robust data management and analytical capabilities, researchers can efficiently analyze large datasets, uncover valuable insights, and better understand the patterns and correlations associated with Alzheimer's disease. In this case, we use the GridDB WebAPI. To learn more, refer to the official Web API - GridDB resource. <\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>

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<\/span>#Libraries for basic data manipulation<\/span>\nimport<\/span> <\/span>os<\/span>\nimport<\/span> <\/span>pandas<\/span> <\/span>as<\/span> <\/span>pd<\/span>\nimport<\/span> <\/span>numpy<\/span> <\/span>as<\/span> <\/span>np<\/span>\n\n#Libraries for the webAPI requests<\/span>\nimport<\/span> <\/span>http<\/span>\nhttp<\/span>.<\/span>client<\/span>.<\/span>HTTPConnection<\/span>.<\/span>debuglevel<\/span> =<\/span> 0<\/span>\nimport<\/span> <\/span>json<\/span>\nimport<\/span> <\/span>requests<\/span>\n\nimport<\/span> <\/span>pyarrow<\/span> <\/span>as<\/span> <\/span>pa<\/span>\nimport<\/span> <\/span>pyarrow.csv<\/span> <\/span>as<\/span> <\/span>csv<\/span>\nimport<\/span> <\/span>time<\/span>\n\n## Setting<\/span>\nfrom<\/span> <\/span>IPython.display<\/span> <\/span>import<\/span> Image<\/span>,<\/span> Markdown<\/span>,<\/span>HTML<\/span>,<\/span> display<\/span>\nimport<\/span> <\/span>warnings<\/span>\n# Suppress all warnings<\/span>\nwarnings<\/span>.<\/span>filterwarnings<\/span>(<\/span>'ignore'<\/span>)<\/span>\n#warnings.filterwarnings(\"ignore\", category=pd.errors.SettingWithCopyWarning)<\/span>\nos<\/span>.<\/span>environ<\/span>[<\/span>'OMP_NUM_THREADS'<\/span>]<\/span> =<\/span> '1'<\/span> # to run KMeans clustering without memory leak issues<\/span>\n\n# Visualizations & Unsupervised Learning<\/span>\nimport<\/span> <\/span>folium<\/span>\nimport<\/span> <\/span>matplotlib.pyplot<\/span> <\/span>as<\/span> <\/span>plt<\/span>\nfrom<\/span> <\/span>sklearn.preprocessing<\/span> <\/span>import<\/span> OneHotEncoder<\/span>\nfrom<\/span> <\/span>sklearn.cluster<\/span> <\/span>import<\/span> KMeans<\/span>\nfrom<\/span> <\/span>sklearn.metrics<\/span> <\/span>import<\/span> silhouette_score<\/span>\nfrom<\/span> <\/span>sklearn.preprocessing<\/span> <\/span>import<\/span> StandardScaler<\/span>\nimport<\/span> <\/span>seaborn<\/span> <\/span>as<\/span> <\/span>sns<\/span>\nimport<\/span> <\/span>re<\/span>  # Importing the regex module for parsing<\/span>\nimport<\/span> <\/span>json<\/span>\n\n# Mention your working directory here<\/span>\nos<\/span>.<\/span>chdir<\/span>(<\/span>\"C:<\/span>\\\\<\/span>XX<\/span>\\\\<\/span>\"<\/span>)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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About the Dataset\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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The dataset being used is from the U.S. Department of Health & Human Services. To access the dataset, navigate to the URL - https:\/\/catalog.data.gov\/dataset\/alzheimers-disease-and-healthy-aging-data<\/a>. Use the 'Comma Separated Values' option to download the .csv file.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>
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<\/span># Specify the path to your image file<\/span>\ncurrent_directory<\/span> =<\/span> os<\/span>.<\/span>getcwd<\/span>()<\/span>\n\n# Construct the image path using os.path.join()<\/span>\nimage_path<\/span> =<\/span> os<\/span>.<\/span>path<\/span>.<\/span>join<\/span>(<\/span>current_directory<\/span>,<\/span> 'Intro_Fig2.Dowloading the Alzheimers dataset.png'<\/span>)<\/span>\n\nwidth<\/span> =<\/span> 700<\/span>\n\ndisplay<\/span>(<\/span>Markdown<\/span>(<\/span>\"### Downloading the Alzheimers' Dataset\"<\/span>))<\/span>\n\n# Display the image<\/span>\ndisplay<\/span>(<\/span>Image<\/span>(<\/span>filename<\/span>=<\/span>image_path<\/span>,<\/span> width<\/span>=<\/span>width<\/span>))<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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Downloading the Alzheimers' Dataset\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n
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The Alzheimer's Disease and Healthy Aging Data<\/strong> dataset is a comprehensive resource compiled by the CDC. It focuses on the health and well-being of older Americans and includes a wide range of data on demographics, health conditions, and behaviors. The dataset is sourced from national surveys like BRFSS, NHANES, and NHIS. It emphasizes Alzheimer's disease, covering prevalence, incidence, risk factors, and outcomes. This data is valuable for identifying trends and exploring risk factors related to Alzheimer's. It is also useful in identifying at-risk populations and tracking the effectiveness of public health interventions for older adults.<\/p>\n
Dataset Columns\u00b6<\/a><\/h3>