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Predicting Survival and Recurrence of Lung Ablation Patients Using Deep Learning-Based Automatic Segmentation and Radiomics Analysis.
Cardiovascular and interventional radiology
Nov 27, 2024
PURPOSE: To predict survival and tumor recurrence following image-guided thermal ablation (IGTA) of lung tumors segmented using a deep learning approach.
Applying natural language processing to understand symptoms among older adult home healthcare patients with urinary incontinence.
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Nov 27, 2024
INTRODUCTION: Little is known about the range and frequency of symptoms among older adult home healthcare patients with urinary incontinence, as this information is predominantly contained in clinical notes. Natural language processing can uncover sy...
Artificial intelligence measured 3D lumbosacral body composition and clinical outcomes in rectal cancer patients.
ANZ journal of surgery
Nov 27, 2024
INTRODUCTION: Patient body composition (BC) has been shown to help predict clinical outcomes in rectal cancer patients. Artificial intelligence algorithms have allowed for easier acquisition of BC measurements, creating a comprehensive BC profile in ...
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
Nov 27, 2024
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
Nov 27, 2024
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
Nov 27, 2024
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
Nov 27, 2024
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
Nov 27, 2024
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
Nov 27, 2024
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
Nov 27, 2024
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...
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