AIMC Topic: Longitudinal Studies
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Examining how gamers connect with their avatars to assess their anxiety: A novel artificial intelligence approach.
Acta psychologica
May 2, 2024
Research has supported that a gamer's attachment to their avatar can offer significant insights about their mental health, including anxiety. To assess this hypothesis, longitudinal data from 565 adult and adolescent participants (M = 29.3 years, SD ...
Physical performance strongly predicts all-cause mortality risk in a real-world population of older diabetic patients: machine learning approach for mortality risk stratification.
Frontiers in endocrinology
Apr 30, 2024
BACKGROUND: Prognostic risk stratification in older adults with type 2 diabetes (T2D) is important for guiding decisions concerning advance care planning.
Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning.
PloS one
Apr 25, 2024
The Omicron SARS-CoV-2 variant continues to strain healthcare systems. Developing tools that facilitate the identification of patients at highest risk of adverse outcomes is a priority. The study objectives are to develop population-scale predictive ...
Prospective prediction of anxiety onset in the Canadian longitudinal study on aging (CLSA): A machine learning study.
Journal of affective disorders
Apr 24, 2024
BACKGROUND: Anxiety disorders are among the most common mental health disorders in the middle aged and older population. Because older individuals are more likely to have multiple comorbidities or increased frailty, the impact of anxiety disorders on...
The gut microbiome associates with phenotypic manifestations of post-acute COVID-19 syndrome.
Cell host & microbe
Apr 23, 2024
The mechanisms underlying the many phenotypic manifestations of post-acute COVID-19 syndrome (PACS) are poorly understood. Herein, we characterized the gut microbiome in heterogeneous cohorts of subjects with PACS and developed a multi-label machine ...
Longitudinal assessment of interstitial lung abnormalities on CT in patients with COPD using artificial intelligence-based segmentation: a prospective observational study.
BMC pulmonary medicine
Apr 23, 2024
BACKGROUND: Interstitial lung abnormalities (ILAs) on CT may affect the clinical outcomes in patients with chronic obstructive pulmonary disease (COPD), but their quantification remains unestablished. This study examined whether artificial intelligen...
A deep-learning approach to predict bleeding risk over time in patients on extended anticoagulation therapy.
Journal of thrombosis and haemostasis : JTH
Apr 19, 2024
BACKGROUND: Thus far, all the clinical models developed to predict major bleeding in patients on extended anticoagulation therapy use the baseline predictors to stratify patients into different risk groups. Therefore, these models do not account for ...
Elucidating the influence of familial interactions on geriatric depression: A comprehensive nationwide multi-center investigation leveraging machine learning.
Acta psychologica
Apr 17, 2024
OBJECTIVE: A plethora of studies have unequivocally established the profound significance of harmonious familial relationships on the psychological well-being of the elderly. In this study, we elucidate the intergenerational relationships, probing th...
Outcome measures applied to robotic assistive technology for people with cerebral palsy: a pilot study.
Disability and rehabilitation. Assistive technology
Apr 15, 2024
The application of robotic devices is being used as Assistive Technology (AT) for improving rehabilitation interventions. The purposes of this research were to (1) test a novel low-cost robotic AT to support interventions for people with Cerebral Pal...
Development and validation of machine learning models to predict frailty risk for elderly.
Journal of advanced nursing
Apr 11, 2024
AIMS: Early identification and intervention of the frailty of the elderly will help lighten the burden of social medical care and improve the quality of life of the elderly. Therefore, we used machine learning (ML) algorithm to develop models to pred...
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