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- Winblad, B, et al.
(författare)
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Mild cognitive impairment--beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment.
- 2004
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Ingår i: Journal of internal medicine. - : Wiley. - 0954-6820 .- 1365-2796. ; 256:3, s. 240-6
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Forskningsöversikt (refereegranskat)abstract
- The First Key Symposium was held in Stockholm, Sweden, 2-5 September 2003. The aim of the symposium was to integrate clinical and epidemiological perspectives on the topic of Mild Cognitive Impairment (MCI). A multidisciplinary, international group of experts discussed the current status and future directions of MCI, with regard to clinical presentation, cognitive and functional assessment, and the role of neuroimaging, biomarkers and genetics. Agreement on new perspectives, as well as recommendations for management and future research were discussed by the international working group. The specific recommendations for the general MCI criteria include the following: (i) the person is neither normal nor demented; (ii) there is evidence of cognitive deterioration shown by either objectively measured decline over time and/or subjective report of decline by self and/or informant in conjunction with objective cognitive deficits; and (iii) activities of daily living are preserved and complex instrumental functions are either intact or minimally impaired.
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- Forsell, Y, et al.
(författare)
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Prevalence and correlates of depression in a population of nonagenarians
- 1995
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Ingår i: British Journal of Psychiatry. - : Royal College of Psychiatrists. - 0007-1250 .- 1472-1465. ; 167:1, s. 61-64
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND Clinicians see many more nonagenarian patients now and there is a need for epidemiological data relating to this group. The aim of the present study was to investigate the prevalence of depressive symptoms and syndromes in this age group.METHOD The DSM-IV and the ICD-10 criteria for depression were used and correlated with physical health, disability in daily life, gender, use of drugs, social circumstances and cognitive dysfunction. Data were derived from 329 persons aged 90 and over, registered in a parish of Stockholm, who had been extensively examined by physicians and nurses.RESULTS/CONCLUSIONS The prevalence of Major Depressive Episode as defined in DSM-IV was 7.9%; and of mild, moderate and severe Depressive Episode (combined); as defined in ICD-10 9.1%. No gender difference was found. Disability in daily life and the use of psychotropic drugs were found to correlate with depressive symptoms and syndromes.
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- Kuo, NIH, et al.
(författare)
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The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms
- 2022
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Ingår i: Scientific data. - : Springer Science and Business Media LLC. - 2052-4463. ; 9:1, s. 693-
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, the machine learning research community has benefited tremendously from the availability of openly accessible benchmark datasets. Clinical data are usually not openly available due to their confidential nature. This has hampered the development of reproducible and generalisable machine learning applications in health care. Here we introduce the Health Gym - a growing collection of highly realistic synthetic medical datasets that can be freely accessed to prototype, evaluate, and compare machine learning algorithms, with a specific focus on reinforcement learning. The three synthetic datasets described in this paper present patient cohorts with acute hypotension and sepsis in the intensive care unit, and people with human immunodeficiency virus (HIV) receiving antiretroviral therapy. The datasets were created using a novel generative adversarial network (GAN). The distributions of variables, and correlations between variables and trends in variables over time in the synthetic datasets mirror those in the real datasets. Furthermore, the risk of sensitive information disclosure associated with the public distribution of the synthetic datasets is estimated to be very low.
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- Truong, Quoc Cuong, et al.
(författare)
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Establishing conversion of the 16-item Informant Questionnaire on Cognitive Decline in the Elderly scores into interval-level data across multiple samples using Rasch methodology
- 2023
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Ingår i: Psychogeriatrics. - : Wiley. - 1346-3500 .- 1479-8301. ; 23:3, s. 411-421
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Tidskriftsartikel (refereegranskat)abstract
- Background: The 16-item Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE-16) is a well-validated and widely-used measure of cognitive changes (CCs) among older adults. This study aimed to use Rasch methodology to establish psychometric properties of the IQCODE-16 and validate the existing ordinal-to-interval transformation algorithms across multiple large samples. Methods: A Partial Credit Rasch model was employed to examine psychometric properties of the IQCODE-16 using data (n = 918) from two longitudinal studies of participants aged 57–99 years: the Older Australian Twins Study (n = 450) and the Canberra Longitudinal Study (n = 468), and reusing the Sydney Memory and Ageing Study (MAS) sample (n = 400). Results: Initial analyses indicated good reliability for the IQCODE-16 (Person Separation Index range: 0.82–0.90). However, local dependency was identified between items, with several items showing misfit to the model. Replicating the existing Rasch solution could not reproduce the best Rasch model fit for all samples. Combining locally dependent items into three testlets resolved all misfit and local dependency issues and resulted in the best Rasch model fit for all samples with evidence of unidimensionality, strong reliability, and invariance across person factors. Accordingly, new ordinal-to-interval transformation algorithms were produced to convert the IQCODE-16 ordinal scores into interval data to improve the accuracy of its scores. Conclusions: The findings of this study support the reliability and validity of the IQCODE-16 in measuring CCs among older adults. New ordinal-to-interval conversion tables generated using samples from multiple independent datasets are more generalizable and can be used to enhance the precision of the IQCODE-16 without changing its original format. An easy-to-use converter has been made available for clinical and research use.
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