Deep learning-based classification of dementia using image representation of subcortical signals.

Journal: BMC medical informatics and decision making
PMID: 40050853

Abstract

BACKGROUND: Dementia is a neurological syndrome marked by cognitive decline. Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the common forms of dementia, each with distinct progression patterns. Early and accurate diagnosis of dementia cases (AD and FTD) is crucial for effective medical care, as both conditions have similar early-symptoms. EEG, a non-invasive tool for recording brain activity, has shown potential in distinguishing AD from FTD and mild cognitive impairment (MCI).

Authors

  • Shivani Ranjan
    Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
  • Ayush Tripathi
    Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
  • Harshal Shende
    Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
  • Robin Badal
    Department of RS and BK, All India Institute of Ayurveda Delhi, New Delhi, India.
  • Amit Kumar
    Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA.
  • Pramod Yadav
    Department of RS and BK, All India Institute of Ayurveda Delhi, New Delhi, India.
  • Deepak Joshi
    Center for Biomedical Engineering, Indian Institute of Technology, Delhi, India.
  • Lalan Kumar

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