AIMC Topic: Aged, 80 and over
Clear Filters Showing 291 to 300 of 3428 articles
Detection of Ocular Surface Squamous Neoplasia Using Artificial Intelligence With Anterior Segment Optical Coherence Tomography.
American journal of ophthalmology
Feb 19, 2025
PURPOSE: To develop and validate a deep learning (DL) model to differentiate ocular surface squamous neoplasia (OSSN) from pterygium and pinguecula using high-resolution anterior segment optical coherence tomography (AS-OCT).
Sensitivity and Specificity
Male
Middle Aged
Deep Learning
Diagnosis, Differential
Reproducibility of Results
Aged
Aged, 80 and over
Adult
Conjunctival Neoplasms
Humans
Artificial Intelligence
Retrospective Studies
Female
Carcinoma, Squamous Cell
Tomography, Optical Coherence
Anterior Eye Segment
Corneal Diseases
Pterygium
Characterizing Brain-Cardiovascular Aging Using Multiorgan Imaging and Machine Learning.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Feb 19, 2025
The structure and function of the brain and cardiovascular system change over the lifespan. In this study, we aim to establish the extent to which age-related changes in these two vital organs are linked. Utilizing normative models and data from the ...
Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatch.
Scientific reports
Feb 18, 2025
The presence of a diffusion-weighted imaging (DWI)-fluid-attenuated inversion recovery (FLAIR) mismatch holds potential value in identifying candidates for recanalization treatment. However, the visual assessment of DWI-FLAIR mismatch is subject to l...
Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.
Scientific reports
Feb 18, 2025
This study examined mental health disparities among African Americans using AI and machine learning for outcome prediction. Analyzing data from African American adults (18-85) in Southeastern Virginia (2016-2020), we found Mood Affective Disorders we...
Predicting diabetes self-management education engagement: machine learning algorithms and models.
BMJ open diabetes research & care
Feb 18, 2025
INTRODUCTION: Diabetes self-management education (DSME) is endorsed by the American Diabetes Association (ADA) as an essential component of diabetes management. However, the utilization of DSME remains limited in the USA. This study aimed to investig...
Robot-Assisted Approach to Diabetes Care Consultations: Enhancing Patient Engagement and Identifying Therapeutic Issues.
Medicina (Kaunas, Lithuania)
Feb 17, 2025
: Diabetes is a rapidly increasing global health challenge compounded by a critical shortage of diabetes care and education specialists. Robot-assisted diabetes care offers a cost-effective and scalable alternative to traditional methods such as trai...
Towards clinical prediction with transparency: An explainable AI approach to survival modelling in residential aged care.
Computer methods and programs in biomedicine
Feb 15, 2025
BACKGROUND AND OBJECTIVE: Scalable, flexible and highly interpretable tools for predicting mortality in residential aged care facilities for the purpose of informing and optimizing palliative care decisions, do not exist. This study is the first and ...
Comparison of AI-based retinal fluid monitoring in neovascular age-related macular degeneration with manual assessment by different eye care professionals under optimized conditions.
Acta ophthalmologica
Feb 14, 2025
PURPOSE: To investigate whether automated intra- and subretinal fluid (IRF/SRF) volume measurements are equivalent to manual evaluations by eye care professionals from different backgrounds on real-world optical coherence tomography (OCT) images in n...
Survival machine learning model of T1 colorectal postoperative recurrence after endoscopic resection and surgical operation: a retrospective cohort study.
BMC cancer
Feb 14, 2025
OBJECTIVE: To construct a postoperative recurrence prediction model for patients with T1 colorectal cancer after endoscopic resection and surgical operation via survival machine learning algorithms.
Comparison of logistic regression and machine learning methods for predicting depression risks among disabled elderly individuals: results from the China Health and Retirement Longitudinal Study.
BMC psychiatry
Feb 14, 2025
BACKGROUND: Given the accelerated aging population in China, the number of disabled elderly individuals is increasing, and depression is a common mental disorder among older adults. This study aims to establish an effective model for predicting depre...
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