AIMC Topic: Retrospective Studies
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Machine-learning tool for classifying pulmonary hypertension via expert reader-provided CT features: An educational resource for non-dedicated radiologists.
European journal of radiology
Feb 15, 2025
PURPOSE: Pulmonary hypertension (PH) is a complex disease classified into five groups (I-V) by the European Society of Cardiology/European Respiratory Society (ESC/ERS) guidelines. Chest contrast-enhanced computed tomography (CECT) is crucial in the ...
Utilization of machine learning algorithm in the prediction of rehospitalization during one-year post traumatic spinal cord injury.
Spinal cord
Feb 15, 2025
STUDY DESIGN: Retrospective cohort study.
Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery.
Cardiovascular diabetology
Feb 15, 2025
BACKGROUND: The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term chronic glycemic factors on stress hyperglycemia levels, which was associated with adverse clinical outcomes. This study aims to evaluate the relationsh...
Female
Stress, Physiological
Risk Factors
Aged
Hyperglycemia
Risk Assessment
Decision Support Techniques
Humans
Male
Treatment Outcome
Blood Glucose
Machine Learning
Databases, Factual
Middle Aged
Predictive Value of Tests
Time Factors
Biomarkers
Cause of Death
Hospital Mortality
Retrospective Studies
Cardiac Surgical Procedures
Development of a diagnostic classification model for lateral cephalograms based on multitask learning.
BMC oral health
Feb 15, 2025
OBJECTIVES: This study aimed to develop a cephalometric classification method based on multitask learning for eight diagnostic classifications.
Artificial intelligence can extract important features for diagnosing axillary lymph node metastasis in early breast cancer using contrast-enhanced ultrasonography.
Scientific reports
Feb 15, 2025
Contrast-enhanced ultrasound (CEUS) plays a pivotal role in the diagnosis of primary breast cancer and in axillary lymph node (ALN) metastasis. However, the imaging features that are clinically crucial for lymph node metastasis have not been fully el...
Prediction of thyroid malignancy risk using clinical and ultrasonography features and a machine learning approach.
European radiology
Feb 14, 2025
OBJECTIVE: This study aims to develop and validate a predictive model for thyroid nodule malignancy risks using clinical and ultrasonography features and a machine learning (ML) approach.
CT-based detection of clinically significant portal hypertension predicts post-hepatectomy outcomes in hepatocellular carcinoma.
European radiology
Feb 14, 2025
BACKGROUND: While the CT-based method of detecting clinically significant portal hypertension (CSPH) emerged as a noninvasive alternative for evaluating CSPH, its predictive ability for post-hepatectomy outcomes is unknown. Therefore, this study aime...
A Bi-modal Temporal Segmentation Network for Automated Segmentation of Focal Liver Lesions in Dynamic Contrast-enhanced Ultrasound.
Ultrasound in medicine & biology
Feb 14, 2025
OBJECTIVE: To develop and validate an automated deep learning-based model for focal liver lesion (FLL) segmentation in a dynamic contrast-enhanced ultrasound (CEUS) video.
The diagnostic performance of automatic B-lines detection for evaluating pulmonary edema in the emergency department among novice point-of-care ultrasound practitioners.
Emergency radiology
Feb 14, 2025
PURPOSE: B-lines in lung ultrasound have been a critical clue for detecting pulmonary edema. However, distinguishing B-lines from other artifacts is a challenge, especially for novice point of care ultrasound (POCUS) practitioners. This study aimed t...
Preoperatively predicting failure to achieve the minimum clinically important difference and the substantial clinical benefit in patient-reported outcome measures for total hip arthroplasty patients using machine learning.
BMC musculoskeletal disorders
Feb 14, 2025
BACKGROUND: Attention to the collection of patient-reported outcomes measures (PROMs) associated with total hip arthroplasty (THA) is growing. The aim of this study was to preoperatively predict failure to achieve the minimal clinically important dif...
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