An explainable machine learning model of cognitive decline derived from speech
INTRODUCTION Traditional Alzheimer's disease (AD) and mild cognitive impairment (MCI)
screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive …
screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive …
An explainable machine learning model of cognitive decline derived from speech
C Chandler, C Diaz-Asper… - Alzheimer's & …, 2023 - pubmed.ncbi.nlm.nih.gov
Introduction Traditional Alzheimer's disease (AD) and mild cognitive impairment (MCI)
screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive …
screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive …
An explainable machine learning model of cognitive decline derived from speech.
C Chandler, C Diaz‐Asper, RS Turner… - Alzheimer's & …, 2023 - search.ebscohost.com
INTRODUCTION: Traditional Alzheimer's disease (AD) and mild cognitive impairment (MCI)
screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive …
screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive …
An explainable machine learning model of cognitive decline derived from speech
C Chandler, C Diaz-Asper, RS Turner, B Reynolds… - 2023 - munin.uit.no
Introduction: Traditional Alzheimer's disease (AD) and mild cognitive impairment (MCI)
screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive …
screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive …
An explainable machine learning model of cognitive decline derived from speech.
C Chandler, C Diaz-Asper, RS Turner… - Alzheimer's & …, 2023 - europepmc.org
Methods Speech collected over the telephone from 91 older participants who were
cognitively healthy (n= 29) or had diagnoses of AD (n= 30) or amnestic MCI (aMCI; n= 32) …
cognitively healthy (n= 29) or had diagnoses of AD (n= 30) or amnestic MCI (aMCI; n= 32) …
[HTML][HTML] An explainable machine learning model of cognitive decline derived from speech
C Chandler, C Diaz‐Asper, RS Turner… - … & Disease Monitoring, 2023 - ncbi.nlm.nih.gov
METHODS Speech collected over the telephone from 91 older participants who were
cognitively healthy (n= 29) or had diagnoses of AD (n= 30) or amnestic MCI (aMCI; n= 32) …
cognitively healthy (n= 29) or had diagnoses of AD (n= 30) or amnestic MCI (aMCI; n= 32) …
An explainable machine learning model of cognitive decline derived from speech
C Chandler, C Diaz-Asper, RS Turner… - Alzheimer's & …, 2023 - search.proquest.com
METHODS Speech collected over the telephone from 91 older participants who were
cognitively healthy (n= 29) or had diagnoses of AD (n= 30) or amnestic MCI (aMCI; n= 32) …
cognitively healthy (n= 29) or had diagnoses of AD (n= 30) or amnestic MCI (aMCI; n= 32) …
An explainable machine learning model of cognitive decline derived from speech.
C Chandler, C Diaz-Asper, RS Turner… - Alzheimer's & …, 2023 - europepmc.org
Methods Speech collected over the telephone from 91 older participants who were
cognitively healthy (n= 29) or had diagnoses of AD (n= 30) or amnestic MCI (aMCI; n= 32) …
cognitively healthy (n= 29) or had diagnoses of AD (n= 30) or amnestic MCI (aMCI; n= 32) …