AIMC Topic: Aged

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Development and validation of a rheumatoid arthritis case definition: a machine learning approach using data from primary care electronic medical records.

BMC medical informatics and decision making
BACKGROUND: Rheumatoid Arthritis (RA) is a chronic inflammatory disease that is primarily diagnosed and managed by rheumatologists; however, it is often primary care providers who first encounter RA-related symptoms. This study developed and validate...

F-FDG PET/CT-based habitat radiomics combining stacking ensemble learning for predicting prognosis in hepatocellular carcinoma: a multi-center study.

BMC cancer
BACKGROUND: This study aims to develop habitat radiomic models to predict overall survival (OS) for hepatocellular carcinoma (HCC), based on the characterization of the intratumoral heterogeneity reflected in F-FDG PET/CT images.

MRI-based radiomic and machine learning for prediction of lymphovascular invasion status in breast cancer.

BMC medical imaging
OBJECTIVE: Lymphovascular invasion (LVI) is critical for the effective treatment and prognosis of breast cancer (BC). This study aimed to investigate the value of eight machine learning models based on MRI radiomic features for the preoperative predi...

Predicting executive functioning from walking features in Parkinson's disease using machine learning.

Scientific reports
Parkinson's disease is characterized by motor and cognitive deficits. While previous work suggests a relationship between both, direct empirical evidence is scarce or inconclusive. Therefore, we examined the relationship between walking features and ...

Assessing Visitor Expectations of AI Nursing Robots in Hospital Settings: Cross-Sectional Study Using the Kano Model.

JMIR nursing
BACKGROUND: Globally, the rates at which the aging population and the prevalence of chronic diseases are increasing are substantial. With declining birth rates and a growing percentage of older individuals, the demand for nursing staff is steadily ri...

Distinguishing among standing postures with machine learning-based classification algorithms.

Experimental brain research
The purpose of our study was to evaluate the accuracy with which classification algorithms could distinguish among standing postures based on center-of-pressure (CoP) trajectories. We performed a secondary analysis of published data from three studie...

Automatic Segmentation of Abdominal Aortic Aneurysms From Time-Resolved 3-D Ultrasound Images Using Deep Learning.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Abdominal aortic aneurysms (AAAs) are rupture-prone dilatations of the aorta. In current clinical practice, the maximal diameter of AAAs is monitored with 2-D ultrasound to estimate their rupture risk. Recent studies have shown that 3-D and mechanica...

Screening for frequent hospitalization risk among community-dwelling older adult between 2016 and 2023: machine learning-driven item selection, scoring system development, and prospective validation.

Frontiers in public health
BACKGROUND: Screening for frequent hospitalizations in the community can help prevent super-utilizers from growing in the inpatient population. However, the determinants of frequent hospitalizations have not been systematically examined, their operat...

Analysis of the Predictors of Mortality from Ischemic Heart Diseases in the Southern Region of Brazil: A Geographic Machine-Learning-Based Study.

Global heart
BACKGROUND: Mortality due to ischemic heart disease (IHD) is heterogeneously distributed globally, and identifying the sites most affected by it is essential in developing strategies to mitigate the impact of the disease, despite the complexity resul...

[The critique of an artificial intelligence tool in the assessment of peripheral facial paralysis].

Annales de chirurgie plastique et esthetique
Peripheral facial palsy (PFP) is an alteration in the functioning of some facial muscles following an injury to the facial nerve. This pathology has functional and aesthetic consequences that impact the quality of life of patients. Their care is esse...