Longitudinal detection of dementia through lexical and syntactic changes in writing: a case study of three British novelists

Le, Xuan Hung; Lancashire, Ian; Hirst, Graeme; Jokel, Regina

doi:10.1093/llc/fqr013

Cited by 168 publications

(121 citation statements)

References 12 publications

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“…Those nuns who met criteria for dementia had lower grammatical complexity scores and lower "idea density" in their autobiographies. Le et al (2011) performed a longitudinal analysis of the writing styles of three novelists: Iris Murdoch who died with Alzheimer's disease (AD), Agatha Christie (suspected AD), and P.D. James (normal brain aging).…”

Section: Related Workmentioning

confidence: 99%

Detecting Dementia through Retrospective Analysis of Routine Blog Posts by Bloggers with Dementia

Masrani¹,

Murray²,

Field³

et al. 2017

BioNLP 2017

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We investigate if writers with dementia can be automatically distinguished from those without by analyzing linguistic markers in written text, in the form of blog posts. We have built a corpus of several thousand blog posts, some by people with dementia and others by people with loved ones with dementia. We use this dataset to train and test several machine learning methods, and achieve prediction performance at a level far above the baseline.

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Section: Related Workmentioning

confidence: 99%

Detecting Dementia through Retrospective Analysis of Routine Blog Posts by Bloggers with Dementia

Masrani¹,

Murray²,

Field³

et al. 2017

BioNLP 2017

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“…There is some evidence, however, that analysis of patients' language may contribute to detecting dementia risk in patients with mild cognitive impairment [5][6][7], in sponaneous writing [8][9][10], and spontaneous speech [11,12].…”

Section: Introduction/backgroundmentioning

confidence: 99%

Towards diagnostic conversational profiles of patients presenting with dementia or functional memory disorders to memory clinics

Elsey

Drew

Jones

et al. 2015

Patient Education and Counseling

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YesObjective\ud \ud This study explores whether the profile of patients’ interactional behaviour in memory clinic conversations with a doctor can contribute to the clinical differentiation between functional memory disorders (FMD) and memory problems related to neurodegenerative diseases.\ud \ud Methods\ud \ud Conversation Analysis of video recordings of neurologists’ interactions with patients attending a specialist memory clinic. “Gold standard” diagnoses were made independently of CA findings by a multi-disciplinary team based on clinical assessment, neuropsychological testing and brain imaging.\ud \ud Results\ud \ud Two discrete conversational profiles for patients with memory complaints emerged, including (i) who attends the clinic (i.e., whether or not patients are accompanied), and (ii) patients’ responses to neurologists’ questions about memory problems, such as difficulties with compound questions and providing specific and elaborated examples and frequent “I don’t know” responses.\ud \ud Conclusion\ud \ud Specific communicative difficulties are characteristic of the interaction patterns of patients with a neurodegenerative pathology. Those difficulties are manifest in memory clinic interactions with neurologists, thereby helping to differentiate patients with dementia from those with FMD.\ud \ud Practical implications\ud \ud Our findings demonstrate that conversational profiles based on patients’ contributions to memory clinic encounters have diagnostic potential to assist the screening and referral process from primary care, and the diagnostic service in secondary care

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“…Lexical analysis of spontaneous speech may also indicate different types of dementia (Bucks et al, 2000;Holmes and Singh, 1996) and may be exploited in the automatic detection of patients suffering from dementia (Thomas et al, 2005). As for analyzing written language, changes in the writing style of people may also refer to dementia (Garrard et al, 2005;Hirst and Wei Feng, 2012;Le et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Detecting Mild Cognitive Impairment by Exploiting Linguistic Information from Transcripts

Vincze

Gosztolya

Tóth

et al. 2016

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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Here we seek to automatically identify Hungarian patients suffering from mild cognitive impairment (MCI) based on linguistic features collected from their speech transcripts. Our system uses machine learning techniques and is based on several linguistic features like characteristics of spontaneous speech as well as features exploiting morphological and syntactic parsing. Our results suggest that it is primarily morphological and speechbased features that help distinguish MCI patients from healthy controls.

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Longitudinal detection of dementia through lexical and syntactic changes in writing: a case study of three British novelists

Cited by 168 publications

References 12 publications

Detecting Dementia through Retrospective Analysis of Routine Blog Posts by Bloggers with Dementia

Detecting Dementia through Retrospective Analysis of Routine Blog Posts by Bloggers with Dementia

Towards diagnostic conversational profiles of patients presenting with dementia or functional memory disorders to memory clinics

Detecting Mild Cognitive Impairment by Exploiting Linguistic Information from Transcripts

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