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Machine Learning Based Algorithms for Virtual Early Detection and Screening of Neurodegenerative and Neurocognitive Disorders: A Systematic-Review Publisher



Yousefi M1 ; Akhbari M2 ; Mohamadi Z3 ; Karami S4 ; Dasoomi H5 ; Atabi A6 ; Sarkeshikian SA7 ; Abdoullahi Dehaki M8 ; Bayati H9 ; Mashayekhi N10 ; Varmazyar S11 ; Rahimian Z12 ; Asadi Anar M13 ; Shafiei D14 Show All Authors
Authors
  1. Yousefi M1
  2. Akhbari M2
  3. Mohamadi Z3
  4. Karami S4
  5. Dasoomi H5
  6. Atabi A6
  7. Sarkeshikian SA7
  8. Abdoullahi Dehaki M8
  9. Bayati H9
  10. Mashayekhi N10
  11. Varmazyar S11
  12. Rahimian Z12
  13. Asadi Anar M13
  14. Shafiei D14
  15. Mohebbi A15
Show Affiliations
Authors Affiliations
  1. 1. Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
  2. 2. Faculty of Medicine, Istanbul Yeni Yuzyil University, Istanbul, Turkey
  3. 3. School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
  4. 4. School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Student Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
  6. 6. School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
  7. 7. School of Medicine, Shahid Beheshti University of Medical Science, Tehran, Iran
  8. 8. Master’s of AI Engineering, Islamic Azad University Tehran Science and Research Branch, Tehran, Iran
  9. 9. Department of Radiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  10. 10. Department of Neuroscience, Bahcesehir University, Istanbul, Turkey
  11. 11. School of Medicine, Shahroud University of Medical Sciences, Shahrud, Iran
  12. 12. School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
  13. 13. Student Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  14. 14. School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  15. 15. Students Research Committee, Ardabil University of Medical Sciences, Ardabil, Iran

Source: Frontiers in Neurology Published:2024


Abstract

Background and aim: Neurodegenerative disorders (e.g., Alzheimer’s, Parkinson’s) lead to neuronal loss; neurocognitive disorders (e.g., delirium, dementia) show cognitive decline. Early detection is crucial for effective management. Machine learning aids in more precise disease identification, potentially transforming healthcare. This comprehensive systematic review discusses how machine learning (ML), can enhance early detection of these disorders, surpassing traditional diagnostics’ constraints. Methods: In this review, databases were examined up to August 15th, 2023, for ML data on neurodegenerative and neurocognitive diseases using PubMed, Scopus, Google Scholar, and Web of Science. Two investigators used the RAYYAN intelligence tool for systematic reviews to conduct the screening. Six blinded reviewers reviewed titles/abstracts. Cochrane risk of bias tool was used for quality assessment. Results: Our search found 7,069 research studies, of which 1,365 items were duplicates and thus removed. Four thousand three hundred and thirty four studies were screened, and 108 articles met the criteria for inclusion after preprocessing. Twelve ML algorithms were observed for dementia, showing promise in early detection. Eighteen ML algorithms were identified for Parkinson’s, each effective in detection and diagnosis. Studies emphasized that ML algorithms are necessary for Alzheimer’s to be successful. Fourteen ML algorithms were discovered for mild cognitive impairment, with LASSO logistic regression being the only one with unpromising results. Conclusion: This review emphasizes the pressing necessity of integrating verified digital health resources into conventional medical practice. This integration may signify a new era in the early detection of neurodegenerative and neurocognitive illnesses, potentially changing the course of these conditions for millions globally. This study showcases specific and statistically significant findings to illustrate the progress in the area and the prospective influence of these advancements on the global management of neurocognitive and neurodegenerative illnesses. Copyright © 2024 Yousefi, Akhbari, Mohamadi, Karami, Dasoomi, Atabi, Sarkeshikian, Abdoullahi Dehaki, Bayati, Mashayekhi, Varmazyar, Rahimian, Asadi Anar, Shafiei and Mohebbi.
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