AIMC Topic: Aged

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Improving the Efficacy of ACR TI-RADS Through Deep Learning-Based Descriptor Augmentation.

Journal of digital imaging
Thyroid nodules occur in up to 68% of people, 95% of which are benign. Of the 5% of malignant nodules, many would not result in symptoms or death, yet 600,000 FNAs are still performed annually, with a PPV of 5-7% (up to 30%). Artificial intelligence ...

Federated Learning: A Cross-Institutional Feasibility Study of Deep Learning Based Intracranial Tumor Delineation Framework for Stereotactic Radiosurgery.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning-based segmentation algorithms usually required large or multi-institute data sets to improve the performance and ability of generalization. However, protecting patient privacy is a key concern in the multi-institutional stud...

Improving detection of obstructive coronary artery disease with an artificial intelligence-enabled electrocardiogram algorithm.

Atherosclerosis
BACKGROUND AND AIMS: To evaluate the risk of coronary artery disease (CAD), the traditional approach involves assessing the patient's symptoms, traditional cardiovascular risk factors (CVRFs), and a 12-lead electrocardiogram (ECG). However, currently...

Evaluation of the effectiveness of artificial intelligence for ultrasound guided peripheral nerve and plane blocks in recognizing anatomical structures.

Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft
BACKGROUND: We aimed to assess the accuracy of artificial intelligence (AI) based real-time anatomy identification for ultrasound-guided peripheral nerve and plane block in eight regions in this prospective observational study.

Deep-learning model for predicting physical fitness in possible sarcopenia: analysis of the Korean physical fitness award from 2010 to 2023.

Frontiers in public health
INTRODUCTION: Physical fitness is regarded as a significant indicator of sarcopenia. This study aimed to develop and evaluate a deep-learning model for predicting the decline in physical fitness due to sarcopenia in individuals with potential sarcope...

Deep learning model fusion improves lung tumor segmentation accuracy across variable training-to-test dataset ratios.

Physical and engineering sciences in medicine
This study aimed to investigate the robustness of a deep learning (DL) fusion model for low training-to-test ratio (TTR) datasets in the segmentation of gross tumor volumes (GTVs) in three-dimensional planning computed tomography (CT) images for lung...

Machine learning models of healthcare expenditures predicting mortality: A cohort study of spousal bereaved Danish individuals.

PloS one
BACKGROUND: The ability to accurately predict survival in older adults is crucial as it guides clinical decision making. The added value of using health care usage for predicting mortality remains unexplored. The aim of this study was to investigate ...

The Effects of Stakeholder Perceptions on the Use of Humanoid Robots in Care for Older Adults: Postinteraction Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Efficient use of humanoid social robots in the care for older adults requires precise knowledge of expectations in this area. There is little research in this field that includes the interaction of stakeholders with the robot. Even fewer ...

The Feasibility of Using a Deep Learning-Based Model to Determine Cardiac Computed Tomographic Contrast Dose.

Journal of computer assisted tomography
PURPOSE: This study aimed to predict contrast effects in cardiac computed tomography (CT) from CT localizer radiographs using a deep learning (DL) model and to compare the prediction performance of the DL model with that of conventional models based ...