Isfahan University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share By
Machine and Deep Learning Algorithms for Classifying Different Types of Dementia: A Literature Review Publisher

Summary: Research highlights machine learning’s promise in early dementia diagnosis, but stresses validation and ethical data use. #Dementia #MachineLearning

Noroozi M1 ; Gholami M2 ; Sadeghsalehi H3 ; Behzadi S4 ; Habibzadeh A5, 6 ; Erabi G7 ; Sadatmadani SF8 ; Diyanati M9 ; Rezaee A10 ; Dianati M4 ; Rasoulian P11 ; Khani Siyah Rood Y12 ; Ilati F13 ; Hadavi SM14 Show All Authors
Authors
  1. Noroozi M1
  2. Gholami M2
  3. Sadeghsalehi H3
  4. Behzadi S4
  5. Habibzadeh A5, 6
  6. Erabi G7
  7. Sadatmadani SF8
  8. Diyanati M9
  9. Rezaee A10
  10. Dianati M4
  11. Rasoulian P11
  12. Khani Siyah Rood Y12
  13. Ilati F13
  14. Hadavi SM14
  15. Arbab Mojeni F15
  16. Roostaie M16
  17. Deravi N17

Source: Applied Neuropsychology:Adult Published:2024


Abstract

The cognitive impairment known as dementia affects millions of individuals throughout the globe. The use of machine learning (ML) and deep learning (DL) algorithms has shown great promise as a means of early identification and treatment of dementia. Dementias such as Alzheimer’s Dementia, frontotemporal dementia, Lewy body dementia, and vascular dementia are all discussed in this article, along with a literature review on using ML algorithms in their diagnosis. Different ML algorithms, such as support vector machines, artificial neural networks, decision trees, and random forests, are compared and contrasted, along with their benefits and drawbacks. As discussed in this article, accurate ML models may be achieved by carefully considering feature selection and data preparation. We also discuss how ML algorithms can predict disease progression and patient responses to therapy. However, overreliance on ML and DL technologies should be avoided without further proof. It’s important to note that these technologies are meant to assist in diagnosis but should not be used as the sole criteria for a final diagnosis. The research implies that ML algorithms may help increase the precision with which dementia is diagnosed, especially in its early stages. The efficacy of ML and DL algorithms in clinical contexts must be verified, and ethical issues around the use of personal data must be addressed, but this requires more study. © 2024 Taylor & Francis Group, LLC.
Other Related Docs