AIMC Topic: Aged
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Effect of a novel artificial intelligence-based cecum recognition system on adenoma detection metrics in a screening colonoscopy setting.
Gastrointestinal endoscopy
Sep 18, 2024
BACKGROUND AND AIMS: Cecal intubation in colonoscopy relies on self-reporting. We developed an artificial intelligence-based cecum recognition system (AI-CRS) for post-hoc verification of cecal intubation and explored its impact on adenoma metrics.
Deep Learning Model of Diastolic Dysfunction Risk Stratifies the Progression of Early-Stage Aortic Stenosis.
JACC. Cardiovascular imaging
Sep 18, 2024
BACKGROUND: The development and progression of aortic stenosis (AS) from aortic valve (AV) sclerosis is highly variable and difficult to predict.
Aortic Valve
Predictive Value of Tests
Ventricular Dysfunction, Left
Diastole
Sclerosis
Time Factors
United States
Calcinosis
Aortic Valve Stenosis
Humans
Risk Assessment
Disease Progression
Male
Prognosis
Severity of Illness Index
Ventricular Function, Left
Deep Learning
Female
Echocardiography
Reproducibility of Results
Middle Aged
Risk Factors
Aged
Deep Learning-Based Denoising Enables High-Quality, Fully Diagnostic Neuroradiological Trauma CT at 25% Radiation Dose.
Academic radiology
Sep 18, 2024
RATIONALE AND OBJECTIVES: Traumatic neuroradiological emergencies necessitate rapid and accurate diagnosis, often relying on computed tomography (CT). However, the associated ionizing radiation poses long-term risks. Modern artificial intelligence re...
Two-step deep-learning identification of heel keypoints from video-recorded gait.
Medical & biological engineering & computing
Sep 18, 2024
Accurate and fast extraction of step parameters from video recordings of gait allows for richer information to be obtained from clinical tests such as Timed Up and Go. Current deep-learning methods are promising, but lack in accuracy for many clinica...
Non-traumatic brachial plexopathy identification from routine MRIs: Retrospective studies with deep learning networks.
European journal of radiology
Sep 18, 2024
PURPOSE: This study aims to seek an optimized deep learning model for differentiating non-traumatic brachial plexopathy from routine MRI scans.
Predicting prolonged length of stay following revision total knee arthroplasty: A national database analysis using machine learning models.
International journal of medical informatics
Sep 18, 2024
BACKGROUND: As the number of revision total knee arthroplasty (TKA) continues to rise, close attention has been paid to factors influencing postoperative length of stay (LOS). The aim of this study is to develop generalizable machine learning (ML) al...
DentAge: Deep learning for automated age prediction using panoramic dental X-ray images.
Journal of forensic sciences
Sep 18, 2024
Age estimation plays a crucial role in various fields, including forensic science and anthropology. This study aims to develop and validate DentAge, a deep-learning model for automated age prediction using panoramic dental X-ray images. DentAge was t...
Instrumented timed up and go test and machine learning-based levodopa response evaluation: a pilot study.
Journal of neuroengineering and rehabilitation
Sep 18, 2024
BACKGROUND: The acute levodopa challenge test (ALCT) is a universal method for evaluating levodopa response (LR). Assessment of Movement Disorder Society's Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) is a key step in ALCT, which...
Development and validation of a machine learning-based framework for assessing metabolic-associated fatty liver disease risk.
BMC public health
Sep 18, 2024
BACKGROUND: The existing predictive models for metabolic-associated fatty liver disease (MAFLD) possess certain limitations that render them unsuitable for extensive population-wide screening. This study is founded upon population health examination ...
Patient Perspectives on AI for Mental Health Care: Cross-Sectional Survey Study.
JMIR mental health
Sep 18, 2024
BACKGROUND: The application of artificial intelligence (AI) to health and health care is rapidly increasing. Several studies have assessed the attitudes of health professionals, but far fewer studies have explored the perspectives of patients or the ...
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