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Artificial intelligence-assisted quantitative CT parameters in predicting the degree of risk of solitary pulmonary nodules.
Annals of medicine
Sep 19, 2024
INTRODUCTION: Artificial intelligence (AI) shows promise for evaluating solitary pulmonary nodules (SPNs) on computed tomography (CT). Accurately determining cancer invasiveness can guide treatment. We aimed to investigate quantitative CT parameters ...
Extracorporeal Closed-Loop Respiratory Regulation for Patients With Respiratory Difficulty Using a Soft Bionic Robot.
IEEE transactions on bio-medical engineering
Sep 19, 2024
OBJECTIVE: Respiratory regulation is critical for patients with respiratory dysfunction. Clinically used ventilators can lead to long-term dependence and injury. Extracorporeal assistance approaches such as iron-lung devices provide a noninvasive alt...
Deep radiomics-based prognostic prediction of oral cancer using optical coherence tomography.
BMC oral health
Sep 19, 2024
BACKGROUND: This study aims to evaluate the integration of optical coherence tomography (OCT) and peripheral blood immune indicators for predicting oral cancer prognosis by artificial intelligence.
Machine learning-based prediction of the risk of moderate-to-severe catheter-related bladder discomfort in general anaesthesia patients: a prospective cohort study.
BMC anesthesiology
Sep 19, 2024
BACKGROUND: Catheter-related bladder discomfort (CRBD) commonly occurs in patients who have indwelling urinary catheters while under general anesthesia. And moderate-to-severe CRBD can lead to significant adverse events and negatively impact patient ...
Identifying severe community-acquired pneumonia using radiomics and clinical data: a machine learning approach.
Scientific reports
Sep 19, 2024
Evaluating Community-Acquired Pneumonia (CAP) is crucial for determining appropriate treatment methods. In this study, we established a machine learning model using radiomics and clinical features to rapidly and accurately identify Severe Community-A...
Investigating Older Adults' Use of a Socially Assistive Robot via Time Series Clustering and User Profiling: Descriptive Analysis Study.
JMIR formative research
Sep 19, 2024
BACKGROUND: The aging population and the shortage of geriatric care workers are major global concerns. Socially assistive robots (SARs) have the potential to address these issues, but developing SARs for various types of users is still in its infancy...
Predicting extended hospital stay following revision total hip arthroplasty: a machine learning model analysis based on the ACS-NSQIP database.
Archives of orthopaedic and trauma surgery
Sep 19, 2024
INTRODUCTION: Prolonged length of stay (LOS) following revision total hip arthroplasty (THA) can lead to increased healthcare costs, higher rates of readmission, and lower patient satisfaction. In this study, we investigated the predictive power of m...
Machine learning to predict distant metastasis and prognostic analysis of moderately differentiated gastric adenocarcinoma patients: a novel focus on lymph node indicators.
Frontiers in immunology
Sep 19, 2024
BACKGROUND: Moderately differentiated gastric adenocarcinoma (MDGA) has a high risk of metastasis and individual variation, which strongly affects patient prognosis. Using large-scale datasets and machine learning algorithms for prediction can improv...
The application and clinical translation of the self-evolving machine learning methods in predicting diabetic retinopathy and visualizing clinical transformation.
Frontiers in endocrinology
Sep 19, 2024
OBJECTIVE: This study aims to analyze the application and clinical translation value of the self-evolving machine learning methods in predicting diabetic retinopathy and visualizing clinical outcomes.
Enhanced machine learning models for predicting one-year mortality in individuals suffering from type A aortic dissection.
The Journal of thoracic and cardiovascular surgery
Sep 18, 2024
OBJECTIVE: The study objective was to develop and validate an interpretable machine learning model to predict 1-year mortality in patients with type A aortic dissection, improving risk classification and aiding clinical decision-making.
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