scholarly journals Personalized Early Stage Alzheimer’s Disease Detection: A Case Study of President Reagan’s Speeches

2020 ◽  
Author(s):  
Ning Wang ◽  
Vishal Peddagangireddy ◽  
Fan Luo ◽  
K.P. Subbalakshmi ◽  
R. Chandramouli
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Mental Healthcare ◽  
Statistical Technique ◽  
Health Issues ◽  
Data Set ◽  
Mental Health Issues

AbstractAlzheimer’s disease (AD)-related global healthcare cost is estimated to be $1 trillion by 2050. Currently, there is no cure for this disease; however, clinical studies show that early diagnosis and intervention helps to extend the quality of life and inform technologies for personalized mental healthcare. Clinical research indicates that the onset and progression of Alzheimer’s disease lead to dementia and other mental health issues. As a result, the language capabilities of patient start to decline.In this paper, we show that machine learning-based unsupervised clustering of and anomaly detection with linguistic biomarkers are promising approaches for intuitive visualization and personalized early stage detection of Alzheimer’s disease. We demonstrate this approach on 10 year’s (1980 to 1989) of President Ronald Reagan’s speech data set. Key linguistic biomarkers that indicate early-stage AD are identified. Experimental results show that Reagan had early onset of Alzheimer’s sometime between 1983 and 1987. This finding is corroborated by prior work that analyzed his interviews using a statistical technique. The proposed technique also identifies the exact speeches that reflect linguistic biomarkers for early stage AD.

scholarly journals Cognitive rehabilitation for early stage Alzheimer’s disease: a pilot study with an Irish population

2017 ◽  
Vol 36 (2) ◽  
pp. 105-119 ◽  
Author(s):  
M. E. Kelly ◽  
B. A. Lawlor ◽  
R. F. Coen ◽  
I. H. Robertson ◽  
S. Brennan
Keyword(s):  
Quality Of Life ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Self Efficacy ◽  
Cognitive Rehabilitation ◽  
Early Stage ◽  
Single Subject ◽  
Everyday Functioning ◽  
Post Test

ObjectivesResearch shows that cognitive rehabilitation (CR) has the potential to improve goal performance and enhance well-being for people with early stage Alzheimer’s disease (AD). This single subject, multiple baseline design (MBD) research investigated the clinical efficacy of an 8-week individualised CR intervention for individuals with early stage AD.MethodsThree participants with early stage AD were recruited to take part in the study. The intervention consisted of eight sessions of 60–90 minutes of CR. Outcomes included goal performance and satisfaction, quality of life, cognitive and everyday functioning, mood, and memory self-efficacy for participants with AD; and carer burden, general mental health, quality of life, and mood of carers.ResultsVisual analysis of MBD data demonstrated a functional relationship between CR and improvements in participants’ goal performance. Subjective ratings of goal performance and satisfaction increased from baseline to post-test for three participants and were maintained at follow-up for two. Baseline to post-test quality of life scores improved for three participants, whereas cognitive function and memory self-efficacy scores improved for two.ConclusionsOur findings demonstrate that CR can improve goal performance, and is a socially acceptable intervention that can be implemented by practitioners with assistance from carers between sessions. This study represents one of the promising first step towards filling a practice gap in this area. Further research and randomised-controlled trials are required.

scholarly journals In-depth Insights into Alzheimer's Disease by using Explainable Machine Learning Approach - Existing Hypothesis Confronted

2021 ◽  
Author(s):  
Bojan Bogdanovic ◽  
Tome Eftimov ◽  
Monika Simjanoska
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Negative Influence ◽  
Data Set ◽  
Huge Data ◽  
Depth Analysis ◽  
Shapley Values ◽  
Intelligent Models

Abstract Background: Alzheimer's disease is still a field of research with lots of open questions. The complexity of the disease prevents the early diagnosis before visible symptoms regarding the individual's cognitive capabilities occur. This research presents an in-depth analysis of a huge data set encompassing medical, cognitive and lifestyle's measurements from more than 12,000 individuals. Several hypothesis were established whose validity has been questioned considering the obtained results.Methods: The importance of appropriate experimental design is highly stressed in the research. Thus, a sequence of methods for handling missing data, redundancy, data imbalance, and correlation analysis have been applied for appropriate preprocessing of the data set, and consequently Random Forest and XGBoost models have been trained and evaluated with special attention to the hyperparameters tuning. Both of the models were explained by using the Shapley values produced by the SHAP method.Results: XGBoost produced the best f1-score of 0.84 and as such is considered to be highly competitive among those published in the literature. This achievement, however, was not the main contribution of this paper. This research's goal was to perform global and local interpretability of both the intelligent models and derive valuable conclusions over the established hypothesis. Those methods led to a single scheme which presents either positive, or, negative influence of the values of each of the features whose importance has been confirmed by means of Shapley values. This scheme might be considered as additional source of knowledge for the physicians and other experts whose concern is the exact diagnosis of early stage of Alzheimer's disease.Conclusion: The conclusions derived from the intelligent models interpretability rejected all the established hypothesis. This research clearly showed the importance of Machine learning explainability approach that opens the black box and clearly unveils the relationships among the features and the diagnoses.

scholarly journals Personalized Early Stage Alzheimer’s Disease Detection: A Case Study of President Reagan’s Speeches

2020 ◽  
Author(s):  
Ning Wang ◽  
Fan Luo ◽  
Vishal Peddagangireddy ◽  
Koduvayur Subbalakshmi ◽  
Rajarathnam Chandramouli
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Disease Detection

The Lived Experience of Early-Stage Alzheimer’s Disease: A Three-Year Longitudinal Phenomenological Case Study

2012 ◽  
Vol 43 (2) ◽  
pp. 216-238 ◽  
Author(s):  
Petra Robinson ◽  
Barbro Giorgi ◽  
Sirkka-Liisa Ekman
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Lived Experience ◽  
Early Stage ◽  
Early Years ◽  
Personal Adjustment ◽  
Transitional Phenomenon ◽  
Clinical Stages ◽  
Phenomenological Case Study

Abstract The purpose of this study was to explore how one person experienced the early years of dementia as she was living through the pre-clinical and early clinical stages of Alzheimer’s disease. Interviews were held on four occasions over a period of three years. The data were analyzed using the descriptive phenomenological psychological method, in which the researcher approached the data from a caring perspective. The lived experience of early-stage Alzheimer’s disease showed to be a complex transitional phenomenon that involves a dynamic process of personal adjustment. The process is set in motion as the participant receives the diagnosis and will eventually lead her towards a state of increased openness and receptiveness toward the disease. The results describe this process as it unfolds in the context of the overall experience, and the various adjustments that the participant undertakes. Some reflections concerning the plausible needs of patients with early-stage Alzheimer’s disease are included in the discussion.

A mentally stimulating activities program for the treatment of neuropsychiatric symptoms in Alzheimer’s disease

2019 ◽  
Vol 18 (4) ◽  
pp. 27-37
Author(s):  
Angie L. Sardina, PhD ◽  
Suzanne Fitzsimmons, MSN, ARNP, GNP ◽  
Catherine M. Hoyt, BA ◽  
Linda L. Buettner, PhD
Keyword(s):  
Quality Of Life ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Support Group ◽  
Repeated Measures ◽  
Early Stage ◽  
Neuropsychiatric Symptoms ◽  
Cognitive Status ◽  
Control Group

This study evaluated whether a mentally stimulating activities (MSA) program reduced neuropsychiatric symptoms and improved cognitive status and quality of life, as compared to a support group for persons in the early stage of Alzheimer’s disease (AD). This randomized controlled trial included 81 adults (aged 55+), who were randomly assigned to the MSA group (treatment) or a social support group (control). A repeated measures multivariate analysis of variance (MANOVA) identified that MSA participants significantly reduced apathy (p 0.001) and depressive symptoms (p 0.001), as well as improved cognitive status (p 0.001) and quality of life (p 0.001) as compared to the control group. A structured classroom-style MSA program may be a viable and therapeutic intervention to alleviate neuropsychiatric symptoms, and improve cognitive status and quality of life in early-stage AD.

The ICT4LIFE Project–Design and development of a new information technology platform for patients with Alzheimer's disease

2017 ◽  
Vol 41 (S1) ◽  
pp. S545-S546
Author(s):  
P. Osvath ◽  
V. Voros ◽  
A. Kovacs ◽  
I. Greges ◽  
S. Fekete ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Integrated Care ◽  
Brain Research ◽  
Early Stage ◽  
Real Life ◽  
User Friendly

AimWith an increasingly growing population in Europe, cognitive impairment is a major social and health issue. According to the World Alzheimer Report (WHO, 2014), dementia, including Alzheimer's disease is one of the biggest global public health challenges our generation is facing. There are many efforts at European level to promote active and healthy ageing. This three-year project has the ambition to provide new services for integrated care with breakthrough research and radical innovation by employing user-friendly Information and Communication Technology (ICT) tools, ultimately increasing patients’ quality-of-life and autonomy at home.MethodsICT4Life proposes an innovative platform for integrated care by the use of sensor-based analytics for human behaviour. Novel ICT services are used to determine the relation between cognitive decline, related psychopathological symptoms and the quality-of-life of the patients, and to assess how these affect patients’ and caregivers’ daily living. ICT4Life platform uses advanced sensor-based analytics; to maximize elderly empowerment and self-care abilities thanks to a properly designed and reconfigurable recommendation system that will be able to exploit user-generated data; and to improve decision-making processes in care professionals’ daily activities. All solutions are developed following a user-centred methodology and tested in real-life scenarios.ResultsThe study design and the preliminary results of the ICT4Life project are presented on the poster.ConclusionICT4Life programme develops a solution for individuals with early stage cognitive impairment that will permit doctors and caregivers to extract useful information about patients, while contributing in a user-friendly way to extending their independence.Disclosure of interestCOI: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement N° 690090. Tamas Tenyi and Sandor Fekete are supported by the National Brain Research Program Grant N° NAP KTIA NAP-A-II/12.

Psychometric Validation of the Czech Version of the Quality of Life – Alzheimer’s Disease Scale in Patients with Early-Stage Dementia

2018 ◽  
Vol 46 (1-2) ◽  
pp. 109-118 ◽  
Author(s):  
Helena Kisvetrová ◽  
David Školoudík ◽  
Roman Herzig ◽  
Martin Vališ ◽  
Božena Jurašková ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Convergent Validity ◽  
Early Stage ◽  
Geriatric Depression Scale ◽  
Depression Scale ◽  
Psychometric Validation ◽  
Physical And Mental Health

Background/Aims: The aim of this study was to perform a psychometric validation of the Czech version of the Quality of Life – Alzheimer’s Disease scale (QoL-AD) for patients with early-stage dementia. Methods: The sample included 212 patient-proxy pairs. For convergent validity, the Czech version of the Bristol Activities of Daily Living Scale (BADLS-CZ), the Short Physical Performance Battery (SPPB), and the Geriatric Depression Scale (GDS) were used. Results: The reliability of the QoL-AD for patients and caregivers was good (Cronbach’s α = 0.85, ICC = 0.25–0.54). A positive correlation existed between the QoL-AD and the SPPB, and negative correlations existed between the QoL-AD and the BADLS-CZ as well as between the QoL-AD and the GDS. Factor analysis resulted in a three-factor solution (physical and mental health, family life, and social security). Conclusion: The Czech version of the QoL-AD has good psychometric properties in compliance with international recommendations.

scholarly journals Longitudinal Comparison of Stability and Sensitivity in Quality of Life Scores Among Nursing Home Residents With and Without Diagnoses of Alzheimer’s Disease and Related Dementias

2021 ◽  
Author(s):  
Xuanzi Qin ◽  
Zachary G Baker ◽  
Stephanie Jarosek ◽  
Mark Woodhouse ◽  
Haitao Chu ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Nursing Home ◽  
Functional Status ◽  
Nursing Home Residents ◽  
Data Set ◽  
The Stability ◽  
Linear Probability

Abstract Background and Objectives Prevalence of nursing home residents with Alzheimer’s Disease and Related Dementias (ADRD) has increased along with a growing consensus that person-centered ADRD care in nursing homes should maximize quality of life (QoL). However, concerns about whether residents with ADRD can make appropriate QoL judgements persist. This study assesses the stability and sensitivity of a self-reported, multi-domain well-being QoL measure for nursing home residents with and without ADRD. Research Design and Methods This study linked the 2012-2015 Minnesota Nursing Home Resident QoL and Satisfaction with Care Survey, Minimum Data Set 3.0 (nursing home assessments), and Minnesota Department of Human Services Cost Reports. The QoL survey included cohort-resident pairs who participated for two consecutive years (N=12,949; 8,803 unique residents from 2012-2013, 2013-2014 and 2014-2015 cohorts). Change in QoL between two years was conceptualized as stable when within 1.5 standard deviations of the sample average. We used linear probability models to estimate associations of ADRD/cognitive function scale status with the stability of QoL summary and domain scores (e.g., social engagement) and the absolute change in QoL summary score, controlling for resident and facility characteristics. Results Most (86.82%) residents had stable QoL summary scores. Residents with moderate to severe cognitive impairment, irrespective of ADRD, were less likely to have stable summary scores than cognitively capable residents without ADRD (P<0.001), but associations varied by QoL domains. Among those with stable summary QoL scores, changes in health/functional status were associated with absolute changes in summary QoL score (P<0.001), suggesting sensitivity of the QoL measure. Discussion and Implications QoL scores were similarly stable over time for most residents with and without ADRD diagnoses and were sensitive to changes in health/functional status. This self-reported QoL measure may be appropriate for nursing home residents, regardless of ADRD diagnosis and can efficaciously be recommended to other states.

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