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Predicting 30-day reoperation following primary total knee arthroplasty: machine learning model outperforms the ACS risk calculator.
Medical & biological engineering & computing
Dec 9, 2024
The ACS risk calculator (ARC) has proven less effective in predicting patient-specific risk of early reoperation after primary total knee arthroplasty (TKA), compromising care quality and cost efficiency. This study compared the performance of a mach...
Prediction of Two Year Survival Following Elective Repair of Abdominal Aortic Aneurysms at A Single Centre Using A Random Forest Classification Algorithm.
European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
Dec 9, 2024
OBJECTIVE: The decision to electively repair an abdominal aortic aneurysm (AAA) involves balancing the risk of rupture, peri-procedural death, and life expectancy. Random forest classifiers (RFCs) are powerful machine learning algorithms. The aim of ...
Impact of Inflammation After Cardiac Surgery on 30-Day Mortality and Machine Learning Risk Prediction.
Journal of cardiothoracic and vascular anesthesia
Dec 9, 2024
OBJECTIVES: To investigate the impact of systemic inflammatory response syndrome (SIRS) on 30-day mortality following cardiac surgery and develop a machine learning model to predict SIRS.
Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data.
International journal of medical informatics
Dec 9, 2024
INTRODUCTION: Optimal basal insulin titration for people with type 2 diabetes is vital to effectively reducing the risk of complications. However, a sizeable proportion of people (30-50 %) remain in suboptimal glycemic control six months post-initiat...
Prediction of Visual Acuity After Cataract Surgery by Deep Learning Methods Using Clinical Information and Color Fundus Photography.
Current eye research
Dec 9, 2024
PURPOSE: To examine the performance of deep-learning models that predicts the visual acuity after cataract surgery using preoperative clinical information and color fundus photography (CFP).
Classification of speech arrests and speech impairments during awake craniotomy: a multi-databases analysis.
International journal of computer assisted radiology and surgery
Dec 9, 2024
PURPOSE: Awake craniotomy presents a unique opportunity to map and preserve critical brain functions, particularly speech, during tumor resection. The ability to accurately assess linguistic functions in real-time not only enhances surgical precision...
Automated Segmentation of MRI White Matter Hyperintensities in 8421 Patients with Acute Ischemic Stroke.
AJNR. American journal of neuroradiology
Dec 9, 2024
BACKGROUND AND PURPOSE: To date, only a few small studies have attempted deep learning-based automatic segmentation of white matter hyperintensity (WMH) lesions in patients with cerebral infarction; this issue is complicated because stroke-related le...
Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning.
JCO clinical cancer informatics
Dec 9, 2024
PURPOSE: Breast density is a widely established independent breast cancer risk factor. With the increasing utilization of digital breast tomosynthesis (DBT) in breast cancer screening, there is an opportunity to estimate volumetric breast density (VB...
Influence of renal function on blood pressure control and outcome in thrombolyzed patients after acute ischemic stroke: analysis of the ENCHANTED trial.
Frontiers in endocrinology
Dec 9, 2024
BACKGROUND: The effect of renal impairment in patients who receive intravenous thrombolysis for acute ischemic stroke (AIS) is unclear. We aimed to determine the associations of renal impairment and clinical outcomes and any modification of the effec...
Radiomics-based machine learning for automated detection of Pneumothorax in CT scans.
PloS one
Dec 9, 2024
The increasing complexity of diagnostic imaging often leads to misinterpretations and diagnostic errors, particularly in critical conditions such as pneumothorax. This study addresses the pressing need for improved diagnostic accuracy in CT scans by ...
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