AIMC Topic: Longitudinal Studies
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Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data.
Scientific reports
Jul 30, 2024
Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient for the accurate prognosis of other outcomes, especially when impacted by co-morbidities such as HIV i...
Predicting treatment outcomes in patients with panic disorder: Cross-sectional and two-year longitudinal structural connectome analysis using machine learning methods.
Journal of anxiety disorders
Jul 26, 2024
PURPOSE: This study examined the relationship between structural brain networks and long-term treatment outcomes in patients with panic disorder (PD) using machine learning methods.
What factors preventing the older adults in China from living longer: a machine learning study.
BMC geriatrics
Jul 22, 2024
BACKGROUND: The fact that most older people do not live long means that they do not have more time to pursue self-actualization and contribute value to society. Although there are many studies on the longevity of the elderly, the limitations of tradi...
A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data.
JMIR public health and surveillance
Jul 18, 2024
BACKGROUND: Multimorbidity is a significant public health concern, characterized by the coexistence and interaction of multiple preexisting medical conditions. This complex condition has been associated with an increased risk of COVID-19. Individuals...
Gender-based linguistic differences in letters of recommendation for rhinology fellowship over time: A dual-institutional follow-up study using natural language processing and deep learning.
International forum of allergy & rhinology
Jul 16, 2024
This follow-up dual-institutional and longitudinal study further evaluated for underlying gender biases in LORs for rhinology fellowship. Explicit and implicit linguistic gender bias was found, heavily favoring male applicants.
Examining individual and contextual predictors of disability in Chinese older adults: A machine learning approach.
International journal of medical informatics
Jul 15, 2024
BACKGROUND: There is a large gap of understanding the determinants of disability, especially the contextual characteristics. Therefore, this study aimed to examine the important predictors of disability in Chinese older adults based on the social eco...
A Computed Tomography-Based Fracture Prediction Model With Images of Vertebral Bones and Muscles by Employing Deep Learning: Development and Validation Study.
Journal of medical Internet research
Jul 12, 2024
BACKGROUND: With the progressive increase in aging populations, the use of opportunistic computed tomography (CT) scanning is increasing, which could be a valuable method for acquiring information on both muscles and bones of aging populations.
Levodopa-induced dyskinesia in Parkinson's disease: Insights from cross-cohort prognostic analysis using machine learning.
Parkinsonism & related disorders
Jul 4, 2024
BACKGROUND: Prolonged levodopa treatment in Parkinson's disease (PD) often leads to motor complications, including levodopa-induced dyskinesia (LID). Despite continuous levodopa treatment, some patients do not develop LID symptoms, even in later stag...
Association of Cardiovascular Health With Brain Age Estimated Using Machine Learning Methods in Middle-Aged and Older Adults.
Neurology
Jun 18, 2024
BACKGROUND AND OBJECTIVES: Cardiovascular health (CVH) has been associated with cognitive decline and dementia, but the extent to which CVH affects brain health remains unclear. We investigated the association of CVH, assessed using Life's Essential ...
Visualization of incrementally learned projection trajectories for longitudinal data.
Scientific reports
Jun 12, 2024
Longitudinal studies that continuously generate data enable the capture of temporal variations in experimentally observed parameters, facilitating the interpretation of results in a time-aware manner. We propose IL-VIS (incrementally learned visualiz...
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