AIMC Topic: Aged

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Evolution of hospitalized patient characteristics through the first three COVID-19 waves in Paris area using machine learning analysis.

PloS one
Characteristics of patients at risk of developing severe forms of COVID-19 disease have been widely described, but very few studies describe their evolution through the following waves. Data was collected retrospectively from a prospectively maintain...

Detecting visually significant cataract using retinal photograph-based deep learning.

Nature aging
Age-related cataracts are the leading cause of visual impairment among older adults. Many significant cases remain undiagnosed or neglected in communities, due to limited availability or accessibility to cataract screening. In the present study, we r...

Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging.

NeuroImage
Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heterogeneity in cognitive aging. Identification of these structures is crucial for screening of older adult...

Deep learning-based detection of parathyroid adenoma by Tc-MIBI scintigraphy in patients with primary hyperparathyroidism.

Annals of nuclear medicine
OBJECTIVE: It is important to detect parathyroid adenomas by parathyroid scintigraphy with 99m-technetium sestamibi (Tc-MIBI) before surgery. This study aimed to develop and validate deep learning (DL)-based models to detect parathyroid adenoma in pa...

Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine.

Scientific reports
Temporal dataset shift associated with changes in healthcare over time is a barrier to deploying machine learning-based clinical decision support systems. Algorithms that learn robust models by estimating invariant properties across time periods for ...