AIMC Topic: Retrospective Studies
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Preoperative diagnosis of meningioma sinus invasion based on MRI radiomics and deep learning: a multicenter study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Feb 28, 2025
OBJECTIVE: Exploring the construction of a fusion model that combines radiomics and deep learning (DL) features is of great significance for the precise preoperative diagnosis of meningioma sinus invasion.
Effects of robot-assisted gait training within 1 week after stroke onset on degree of gait independence in individuals with hemiparesis: a propensity score-matched analysis in a single-center cohort study.
Journal of neuroengineering and rehabilitation
Feb 28, 2025
BACKGROUND: Robot-assisted gait training (RAGT) is an effective method for treating gait disorders in individuals with stroke. However, no previous studies have demonstrated the effectiveness of RAGT in individuals with acute stroke. This study aimed...
Relationship between atherogenic index of plasma and length of stay in critically ill patients with atherosclerotic cardiovascular disease: a retrospective cohort study and predictive modeling based on machine learning.
Cardiovascular diabetology
Feb 28, 2025
BACKGROUND: The atherogenic index of plasma (AIP) is considered an important marker of atherosclerosis and cardiovascular risk. However, its potential role in predicting length of stay (LOS), especially in patients with atherosclerotic cardiovascular...
Humans
Machine Learning
Decision Support Techniques
Databases, Factual
Biomarkers
Atherosclerosis
Prognosis
Cholesterol, HDL
Retrospective Studies
Middle Aged
Triglycerides
Critical Illness
Risk Assessment
Length of Stay
Intensive Care Units
Time Factors
Female
Predictive Value of Tests
Risk Factors
Aged
Male
Predicting outcomes of expectant and medical management in early pregnancy miscarriage using machine learning to develop and validate multivariable clinical prediction models.
BMC pregnancy and childbirth
Feb 28, 2025
OBJECTIVE: To determine whether readily available patient, ultrasound and treatment outcome data can be used to develop, validate and externally test two machine learning (ML) models for predicting the success of expectant and medical management of m...
Biomarker and clinical data-based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal study.
BMJ health & care informatics
Feb 27, 2025
OBJECTIVES: To develop a machine learning-based software as a medical device to predict the endurance and outcomes of peritoneal dialysis (PD) patients in real time using effluent-measured biomarkers of the mesothelial-to-mesenchymal transition (MMT)...
Development of an artificial intelligence-based multimodal diagnostic system for early detection of biliary atresia.
BMC medicine
Feb 27, 2025
BACKGROUND: Early diagnosis of biliary atresia (BA) is crucial for improving patient outcomes, yet remains a significant global challenge. This challenge may be ameliorated through the application of artificial intelligence (AI). Despite the promise ...
Prediction of contrast-associated acute kidney injury with machine-learning in patients undergoing contrast-enhanced computed tomography in emergency department.
Scientific reports
Feb 27, 2025
Radiocontrast media is a major cause of nephrotoxic acute kidney injury(AKI). Contrast-enhanced CT(CE-CT) is commonly performed in emergency departments(ED). Predicting individualized risks of contrast-associated AKI(CA-AKI) in ED patients is challen...
Machine learning-driven ultrasound radiomics for assessing axillary lymph node burden in breast cancer.
Frontiers in endocrinology
Feb 27, 2025
OBJECTIVE: This study explores the value of combining intratumoral and peritumoral radiomics features from ultrasound imaging with clinical characteristics to assess axillary lymph node burden in breast cancer patients.
Multi-parametric MRI Habitat Radiomics Based on Interpretable Machine Learning for Preoperative Assessment of Microsatellite Instability in Rectal Cancer.
Academic radiology
Feb 26, 2025
RATIONALE AND OBJECTIVES: This study constructed an interpretable machine learning model based on multi-parameter MRI sub-region habitat radiomics and clinicopathological features, aiming to preoperatively evaluate the microsatellite instability (MSI...
Pre-transplant and transplant parameters predict long-term survival after hematopoietic cell transplantation using machine learning.
Transplant immunology
Feb 26, 2025
BACKGROUND: Allogeneic hematopoietic stem transplantation (allo-HSCT) constitutes a curative treatment for various hematological malignancies. However, various complications limit the therapeutic efficacy of this approach, increasing the morbidity an...
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