AI Medical Compendium Topic:
Aged, 80 and over

Clear Filters Showing 821 to 830 of 3208 articles

Late Life Cognitive Function Trajectory Among the Chinese Oldest-Old Population-A Machine Learning Approach.

Journal of gerontological social work
Informed by the biopsychosocial framework, our study uses the Chinese Longitudinal Healthy Longevity Survey (CLHLS) dataset to examine cognitive function trajectories among the oldest-old (80+). Employing K-means clustering, we identified two latent ...

Development of a deep-learning algorithm for age estimation on CT images of the vertebral column.

Legal medicine (Tokyo, Japan)
PURPOSE: The accurate age estimation of cadavers is essential for their identification. However, conventional methods fail to yield adequate age estimation especially in elderly cadavers. We developed a deep learning algorithm for age estimation on C...

Assessing the Influence of B-US, CDFI, SE, and Patient Age on Predicting Molecular Subtypes in Breast Lesions Using Deep Learning Algorithms.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Our study aims to investigate the impact of B-mode ultrasound (B-US) imaging, color Doppler flow imaging (CDFI), strain elastography (SE), and patient age on the prediction of molecular subtypes in breast lesions.

Multimodal Machine Learning for Prediction of 30-Day Readmission Risk in Elderly Population.

The American journal of medicine
BACKGROUND: Readmission within 30 days is a prevalent issue among elderly patients, linked to unfavorable health outcomes. Our objective was to develop and validate multimodal machine learning models for predicting 30-day readmission risk in elderly ...

Predicting ischemic stroke patients' prognosis changes using machine learning in a nationwide stroke registry.

Medical & biological engineering & computing
Accurately predicting the prognosis of ischemic stroke patients after discharge is crucial for physicians to plan for long-term health care. Although previous studies have demonstrated that machine learning (ML) shows reasonably accurate stroke outco...

Deep learning denoising reconstruction enables faster T2-weighted FLAIR sequence acquisition with satisfactory image quality.

Journal of medical imaging and radiation oncology
INTRODUCTION: Deep learning reconstruction (DLR) technologies are the latest methods attempting to solve the enduring problem of reducing MRI acquisition times without compromising image quality. The clinical utility of this reconstruction technique ...

Real-World Outcomes of Patients with Advanced Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Cancer in Canada Using Data Extracted by Large Language Model-Based Artificial Intelligence.

Current oncology (Toronto, Ont.)
Real-world evidence for patients with advanced -mutated non-small cell lung cancer (NSCLC) in Canada is limited. This study's objective was to use previously validated DARWEN artificial intelligence (AI) to extract data from electronic heath records ...

An Explainable Artificial Intelligence Model to Predict Malignant Cerebral Edema after Acute Anterior Circulating Large-Hemisphere Infarction.

European neurology
INTRODUCTION: Malignant cerebral edema (MCE) is a serious complication and the main cause of poor prognosis in patients with large-hemisphere infarction (LHI). Therefore, the rapid and accurate identification of potential patients with MCE is essenti...