Abstract:
Data science is the process of liberating meaning from raw data using scientific methods and algorithms, and is becoming much more commonly used in healthcare with the em...Show MoreMetadata
Abstract:
Data science is the process of liberating meaning from raw data using scientific methods and algorithms, and is becoming much more commonly used in healthcare with the emergence of personalised healthcare. Alzheimer's disease (AD) is a neurodegenerative disease that has no proven curative treatment, however a new treatment protocol, ReCODE, has been proposed to slow and reverse the progression of the disease. In this paper, an overview of AD is provided, followed by a description of the ReCODE protocol, including the new proposed methods and data to be used in prediction diagnosis and treatment. The ways in which data science can help with prediction and diagnosis are then reviewed, along with the data science techniques that can help with each treatment in the protocol. It is concluded that current data science techniques are useful in aiding the successful treatment of AD patients with he ReCODE protocol, and though there is much promise to the use of data science techniques to predict and diagnose AD, no such technique yet exists that can process all the necessary data. Future research should be conducted to develop such a data science technique. Further research should also be conducted to improve current data science techniques used to support the treatment of AD.
Date of Conference: 07-10 October 2019
Date Added to IEEE Xplore: 23 April 2020
ISBN Information:
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- IEEE Keywords
- Data science ,
- Protocols ,
- Proteins ,
- Dementia ,
- Genetics
- Index Terms
- Data Science Techniques ,
- Alzheimer’s Disease ,
- Personal Health ,
- Alzheimer’s Disease Patients ,
- Treatment Of Alzheimer’s Disease ,
- Insulin ,
- Science And Technology ,
- Blood Glucose Levels ,
- Blood Tests ,
- Inflammation In Patients ,
- Cognitive Training ,
- Alzheimer’s Disease Risk ,
- Diagnosis Of Alzheimer’s Disease ,
- Part Of Diet ,
- Unique Patients ,
- Brain Protein ,
- Amyloid Protein ,
- Ketosis ,
- Carbohydrate Levels ,
- APoE4 Allele ,
- Prediction Of Alzheimer’s Disease ,
- Typical Alzheimer’s Disease ,
- Cause Of Alzheimer’s Disease ,
- Lifestyle Data ,
- Suboptimal Values ,
- Hormone Replacement Therapy ,
- Lifestyle Factors ,
- Destruction Of Neurons ,
- Tau Protein Levels ,
- Neuropsychological Tests
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Data science ,
- Protocols ,
- Proteins ,
- Dementia ,
- Genetics
- Index Terms
- Data Science Techniques ,
- Alzheimer’s Disease ,
- Personal Health ,
- Alzheimer’s Disease Patients ,
- Treatment Of Alzheimer’s Disease ,
- Insulin ,
- Science And Technology ,
- Blood Glucose Levels ,
- Blood Tests ,
- Inflammation In Patients ,
- Cognitive Training ,
- Alzheimer’s Disease Risk ,
- Diagnosis Of Alzheimer’s Disease ,
- Part Of Diet ,
- Unique Patients ,
- Brain Protein ,
- Amyloid Protein ,
- Ketosis ,
- Carbohydrate Levels ,
- APoE4 Allele ,
- Prediction Of Alzheimer’s Disease ,
- Typical Alzheimer’s Disease ,
- Cause Of Alzheimer’s Disease ,
- Lifestyle Data ,
- Suboptimal Values ,
- Hormone Replacement Therapy ,
- Lifestyle Factors ,
- Destruction Of Neurons ,
- Tau Protein Levels ,
- Neuropsychological Tests
- Author Keywords