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A Novel Approach to Predict the Longevity in Alzheimer's Patients Based on Rate of Cognitive Deterioration using Fuzzy Logic Based Feature Extraction Algorithm

  • Sridevi, Mutyala (BMS Institute of Technology and Management) ;
  • B.R., Arun Kumar (BMS Institute of Technology and Management)
  • Received : 2021.08.05
  • Published : 2021.08.30

Abstract

Alzheimer's is a chronic progressive disease which exhibits varied symptoms and behavioural traits from person to person. The deterioration in cognitive abilities is more noticeable through their Activities and Instrumental Activities of Daily Living rather than biological markers. This information discussed in social media communities was collected and features were extracted by using the proposed fuzzy logic based algorithm to address the uncertainties and imprecision in the data reported. The data thus obtained is used to train machine learning models in order to predict the longevity of the patients. Models built on features extracted using the proposed algorithm performs better than models trained on full set of features. Important findings are discussed and Support Vector Regressor with RBF kernel is identified as the best performing model in predicting the longevity of Alzheimer's patients. The results would prove to be of high value for healthcare practitioners and palliative care providers to design interventions that can alleviate the trauma faced by patients and caregivers due to chronic diseases.

Keywords

Acknowledgement

We would like to acknowledge the support by Dr. Meenakshi Banerjee, Ph.D. (National Institute of Mental Health and Neuro Sciences - NIMHANS), Assistant Professor, Jindal School of Psychology and Counselling, O.P. Jindal Global University, for providing the knowledge on geriatric mental health, assessment indexes and assistance in the collection of relevant material, to progress with the research. Her specialized knowledge in Cognitive Behaviour Therapy and work experience in special clinical units such as Adult Psychiatry and Neuropsychology led our research in the right direction.

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