AIMC Topic: Aged

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Weakly-supervised deep learning for ultrasound diagnosis of breast cancer.

Scientific reports
Conventional deep learning (DL) algorithm requires full supervision of annotating the region of interest (ROI) that is laborious and often biased. We aimed to develop a weakly-supervised DL algorithm that diagnosis breast cancer at ultrasound without...

Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation.

NeuroImage
Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been app...

Score and Correlation Coefficient-Based Feature Selection for Predicting Heart Failure Diagnosis by Using Machine Learning Algorithms.

Computational and mathematical methods in medicine
Cardiovascular disease (CVD) is one of the most common causes of death that kills approximately 17 million people annually. The main reasons behind CVD are myocardial infarction and the failure of the heart to pump blood normally. Doctors could diagn...

Ethical issues of smart home-based elderly care: A scoping review.

Journal of nursing management
AIM: To explore current research on the ethics of smart home technologies including artificial intelligence and information technologies for elderly care by conducting a scoping review.

Structural, functional and molecular pathogenesis of pelvic organ prolapse in patient and deficient mice.

Aging
Pelvic organ prolapse is a worldwide health problem to elderly women. Understanding its pathogenesis and an ideal animal model are crucial to developing promising treatments. The present study aimed to investigate new clinical significance and detail...

Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes.

Journal of cardiovascular computed tomography
BACKGROUND: Low-dose computed tomography (LDCT) are performed routinely for lung cancer screening. However, a large amount of nonpulmonary data from these scans remains unassessed. We aimed to validate a deep learning model to automatically segment a...

Evaluation of a Novel Artificial Intelligence System to Monitor and Assess Energy and Macronutrient Intake in Hospitalised Older Patients.

Nutrients
Malnutrition is common, especially among older, hospitalised patients, and is associated with higher mortality, longer hospitalisation stays, infections, and loss of muscle mass. It is therefore of utmost importance to employ a proper method for diet...

Detection of Left Atrial Myopathy Using Artificial Intelligence-Enabled Electrocardiography.

Circulation. Heart failure
BACKGROUND: Left atrial (LA) myopathy is common in patients with heart failure and preserved ejection fraction and leads to the development of atrial fibrillation (AF). We investigated whether the likelihood of LA remodeling, LA dysfunction, altered ...

Prostate Cancer: Early Detection and Assessing Clinical Risk Using Deep Machine Learning of High Dimensional Peripheral Blood Flow Cytometric Phenotyping Data.

Frontiers in immunology
Detecting the presence of prostate cancer (PCa) and distinguishing low- or intermediate-risk disease from high-risk disease early, and without the need for potentially unnecessary invasive biopsies remains a significant clinical challenge. The aim of...