AIMC Topic: Aged, 80 and over
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Identifying Functional Status Impairment in People Living With Dementia Through Natural Language Processing of Clinical Documents: Cross-Sectional Study.
Journal of medical Internet research
Feb 13, 2024
BACKGROUND: Assessment of activities of daily living (ADLs) and instrumental ADLs (iADLs) is key to determining the severity of dementia and care needs among older adults. However, such information is often only documented in free-text clinical notes...
Strong Diagnostic Performance of Single Energy 256-row Multidetector Computed Tomography with Deep Learning Image Reconstruction in the Assessment of Myocardial Fibrosis.
Internal medicine (Tokyo, Japan)
Feb 12, 2024
Objective Although magnetic resonance imaging (MRI) is the gold standard for evaluating abnormal myocardial fibrosis and extracellular volume (ECV) of the left ventricular myocardium (LVM), a similar evaluation has recently become possible using comp...
DeepAlienorNet: A deep learning model to extract clinical features from colour fundus photography in age-related macular degeneration.
Acta ophthalmologica
Feb 12, 2024
OBJECTIVE: This study aimed to develop a deep learning (DL) model, named 'DeepAlienorNet', to automatically extract clinical signs of age-related macular degeneration (AMD) from colour fundus photography (CFP).
nnU-Net-Based Pancreas Segmentation and Volume Measurement on CT Imaging in Patients with Pancreatic Cancer.
Academic radiology
Feb 12, 2024
RATIONALE AND OBJECTIVES: To develop and validate a deep learning (DL)-based method for pancreas segmentation on CT and automatic measurement of pancreatic volume in pancreatic cancer.
Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study.
Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Feb 11, 2024
Elderly patients often have more than one disease that affects walking behavior. An objective tool to identify which disease is the main cause of functional limitations may aid clinical decision making. Therefore, we investigated whether gait pattern...
Artificial intelligence technology improves the accuracy of preoperative planning in primary total hip arthroplasty.
Asian journal of surgery
Feb 10, 2024
OBJECTIVE: Successful total hip arthroplasty relies on accurate preoperative planning. However, the conventional preoperative planning, a two-dimensional method using X-ray template, has shown poor reliability of predicting component size. To our kno...
Assessing Fuchs Corneal Endothelial Dystrophy Using Artificial Intelligence-Derived Morphometric Parameters From Specular Microscopy Images.
Cornea
Feb 9, 2024
PURPOSE: The aim of this study was to evaluate the efficacy of artificial intelligence-derived morphometric parameters in characterizing Fuchs corneal endothelial dystrophy (FECD) from specular microscopy images.
Inconsistency between Human Observation and Deep Learning Models: Assessing Validity of Postmortem Computed Tomography Diagnosis of Drowning.
Journal of imaging informatics in medicine
Feb 9, 2024
Drowning diagnosis is a complicated process in the autopsy, even with the assistance of autopsy imaging and the on-site information from where the body was found. Previous studies have developed well-performed deep learning (DL) models for drowning d...
Multicentric clinical evaluation of a computed tomography-based fully automated deep neural network for aortic maximum diameter and volumetric measurements.
Journal of vascular surgery
Feb 5, 2024
OBJECTIVE: This study aims to evaluate a fully automatic deep learning-based method (augmented radiology for vascular aneurysm [ARVA]) for aortic segmentation and simultaneous diameter and volume measurements.
Development and multicenter validation of deep convolutional neural network-based detection of colorectal cancer on abdominal CT.
European radiology
Feb 1, 2024
OBJECTIVES: This study aims to develop computer-aided detection (CAD) for colorectal cancer (CRC) using abdominal CT based on a deep convolutional neural network.
Neural Networks, Computer
Retrospective Studies
Tomography, X-Ray Computed
Female
Reproducibility of Results
Humans
Male
Middle Aged
Adenocarcinoma
Radiographic Image Interpretation, Computer-Assisted
Radiography, Abdominal
Aged
Aged, 80 and over
Adult
Sensitivity and Specificity
Colorectal Neoplasms
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