Accuracy of dementia diagnosis—A direct comparison between radiologists and a computerized method

Playful jazz improvisations and singing continue in creating the gift of emotional connection in a family living with Alzheimer’s. Sharing their poignant reflections provides a personal account of the centrality of music in reaching each other at a feeling level throughout the course of their lives. The recognition of music as a powerful and creative force for all of us, particularly when there is a dementia diagnosis, is explored.

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Automated Computerized Method for the Detection of Unruptured Cerebral Aneurysms in DSA Images

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405613666170502162130 ◽

2018 ◽

Vol 14 (5) ◽

pp. 771-777 ◽

Cited By ~ 3

Author(s):

Ines Rahmany ◽

Sabrine Laajili ◽

Nawres Khlifa

Keyword(s):

Cerebral Aneurysms ◽

Computerized Method ◽

Unruptured Cerebral Aneurysms

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Mining Social Media Data to Study the Consequences of Dementia Diagnosis on Caregivers and Relatives (Preprint)

10.2196/preprints.10506 ◽

2018 ◽

Author(s):

Anika Oellrich ◽

George Gkotsis ◽

Richard James Butler Dobson ◽

Tim JP Hubbard ◽

Rina Dutta

Keyword(s):

Social Media ◽

Family Relationships ◽

Text Processing ◽

Automated Analysis ◽

Health Concern ◽

Dementia Diagnosis ◽

Data Set ◽

Social Media Data ◽

Real Time Processing ◽

Media Data

BACKGROUND Dementia is a growing public health concern with approximately 50 million people affected worldwide in 2017 and this number is expected to reach more than 131 million by 2050. The toll on caregivers and relatives cannot be underestimated as dementia changes family relationships, leaves people socially isolated, and affects the finances of all those involved. OBJECTIVE The aim of this study was to explore using automated analysis (i) the age and gender of people who post to the social media forum Reddit about dementia diagnoses, (ii) the affected person and their diagnosis, (iii) relevant subreddits authors are posting to, (iv) the types of messages posted and (v) the content of these posts. METHODS We analysed Reddit posts concerning dementia diagnoses. We used a previously developed text analysis pipeline to determine attributes of the posts as well as their authors to characterise online communications about dementia diagnoses. The posts were also examined by manual curation for the diagnosis provided and the person affected. Furthermore, we investigated the communities these people engage in and assessed the contents of the posts with an automated topic gathering technique. RESULTS Our results indicate that the majority of posters in our data set are women, and it is mostly close relatives such as parents and grandparents that are mentioned. Both the communities frequented and topics gathered reflect not only the sufferer's diagnosis but also potential outcomes, e.g. hardships experienced by the caregiver. The trends observed from this dataset are consistent with findings based on qualitative review, validating the robustness of social media automated text processing. CONCLUSIONS This work demonstrates the value of social media data sources as a resource for in-depth studies of those affected by a dementia diagnosis and the potential to develop novel support systems based on their real time processing in line with the increasing digitalisation of medical care.

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General practitioners’ attitude toward early and pre‐dementia diagnosis of AD in five European countries—A MOPEAD project survey

Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring ◽

10.1002/dad2.12130 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Lena Sannemann ◽

Theresa Müller ◽

Lisa Waterink ◽

Marissa Zwan ◽

Anders Wimo ◽

...

Keyword(s):

General Practitioners ◽

European Countries ◽

Dementia Diagnosis

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Predicting dementia diagnosis from cognitive footprints in electronic health records: a case–control study protocol

BMJ Open ◽

10.1136/bmjopen-2020-043487 ◽

2020 ◽

Vol 10 (11) ◽

pp. e043487

Author(s):

Hao Luo ◽

Kui Kai Lau ◽

Gloria H Y Wong ◽

Wai-Chi Chan ◽

Henry K F Mak ◽

...

Keyword(s):

Machine Learning ◽

Risk Factors ◽

Hong Kong ◽

Electronic Health Records ◽

Case Control Study ◽

Case Control ◽

Dementia Diagnosis ◽

Health Records ◽

Electronic Health ◽

Control Study

IntroductionDementia is a group of disabling disorders that can be devastating for persons living with it and for their families. Data-informed decision-making strategies to identify individuals at high risk of dementia are essential to facilitate large-scale prevention and early intervention. This population-based case–control study aims to develop and validate a clinical algorithm for predicting dementia diagnosis, based on the cognitive footprint in personal and medical history.Methods and analysisWe will use territory-wide electronic health records from the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong between 1 January 2001 and 31 December 2018. All individuals who were at least 65 years old by the end of 2018 will be identified from CDARS. A random sample of control individuals who did not receive any diagnosis of dementia will be matched with those who did receive such a diagnosis by age, gender and index date with 1:1 ratio. Exposure to potential protective/risk factors will be included in both conventional logistic regression and machine-learning models. Established risk factors of interest will include diabetes mellitus, midlife hypertension, midlife obesity, depression, head injuries and low education. Exploratory risk factors will include vascular disease, infectious disease and medication. The prediction accuracy of several state-of-the-art machine-learning algorithms will be compared.Ethics and disseminationThis study was approved by Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW 18-225). Patients’ records are anonymised to protect privacy. Study results will be disseminated through peer-reviewed publications. Codes of the resulted dementia risk prediction algorithm will be made publicly available at the website of the Tools to Inform Policy: Chinese Communities’ Action in Response to Dementia project (https://www.tip-card.hku.hk/).

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