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Patient-ventilator asynchrony classification in mechanically ventilated patients: Model-based or machine learning method?
Computer methods and programs in biomedicine
Jul 11, 2024
BACKGROUND AND OBJECTIVE: Patient-ventilator asynchrony (PVA) is associated with poor clinical outcomes and remains under-monitored. Automated PVA detection would enable complete monitoring standard observational methods do not allow. While model-bas...
Analyzing pain patterns in the emergency department: Leveraging clinical text deep learning models for real-world insights.
International journal of medical informatics
Jul 11, 2024
OBJECTIVE: To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm.
Evaluation of risk factors and survival rates of patients with early-stage breast cancer with machine learning and traditional methods.
International journal of medical informatics
Jul 11, 2024
BACKGROUND: This article is aimed to make predictions in terms of prognostic factors and compare prediction methods by using Cox proportional hazards regression analysis (CPH), some machine learning techniques and Accelerated Failure Time (AFT) model...
Deep learning classification performance for diagnosing condylar osteoarthritis in patients with dentofacial deformities using panoramic temporomandibular joint projection images.
Oral radiology
Jul 11, 2024
OBJECTIVE: The present study aimed to assess the consistencies and performances of deep learning (DL) models in the diagnosis of condylar osteoarthritis (OA) among patients with dentofacial deformities using panoramic temporomandibular joint (TMJ) pr...
Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.
Cancer science
Jul 11, 2024
Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of research utilizing big data to predict UM distant metastasis. This study leveraged machine learning metho...
Metabolism score and machine learning models for the prediction of esophageal squamous cell carcinoma progression.
Cancer science
Jul 11, 2024
The incomplete prediction of prognosis in esophageal squamous cell carcinoma (ESCC) patients is attributed to various therapeutic interventions and complex prognostic factors. Consequently, there is a pressing demand for enhanced predictive biomarker...
Predicting Secondary Vertebral Compression Fracture After Vertebral Augmentation via CT-Based Machine Learning Radiomics-Clinical Model.
Academic radiology
Jul 10, 2024
RATIONALE AND OBJECTIVES: Secondary vertebral compression fractures (SVCF) are very common in patients after vertebral augmentation (VA). The aim of this study was to establish a radiomic-based model to predict SVCF and specify appropriate treatment ...
Development of a machine learning-based model for the prediction and progression of diabetic kidney disease: A single centred retrospective study.
International journal of medical informatics
Jul 10, 2024
BACKGROUND: Diabetic kidney disease (DKD) is a diabetic microvascular complication often characterized by an unpredictable progression. Hence, early detection and recognition of patients vulnerable to progression is crucial.
Improving diagnostic confidence in low-dose dual-energy CTE with low energy level and deep learning reconstruction.
European journal of radiology
Jul 10, 2024
OBJECTIVE: To demonstrate the value of using 50 keV virtual monochromatic images with deep learning image reconstruction (DLIR) in low-dose dual-energy CT enterography (CTE).
Improving brain atrophy quantification with deep learning from automated labels using tissue similarity priors.
Computers in biology and medicine
Jul 10, 2024
Brain atrophy measurements derived from magnetic resonance imaging (MRI) are a promising marker for the diagnosis and prognosis of neurodegenerative pathologies such as Alzheimer's disease or multiple sclerosis. However, its use in individualized ass...
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