AIMC Topic: Aged
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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...
Machine Learning
Decision Support Techniques
Databases, Factual
Biomarkers
Prognosis
Retrospective Studies
Critical Illness
Intensive Care Units
Female
Cholesterol, HDL
Triglycerides
Humans
Risk Assessment
Length of Stay
Time Factors
Risk Factors
Predictive Value of Tests
Atherosclerosis
Aged
Male
Middle Aged
ScreenDx, an artificial intelligence-based algorithm for the incidental detection of pulmonary fibrosis.
The American journal of the medical sciences
Feb 27, 2025
BACKGROUND: Nonspecific symptoms and variability in radiographic reporting patterns contribute to a diagnostic delay of the diagnosis of pulmonary fibrosis. An attractive solution is the use of machine-learning algorithms to screen for radiographic f...
Risk factors and an interpretability tool of in-hospital mortality in critically ill patients with acute myocardial infarction.
Clinical medicine (London, England)
Feb 27, 2025
OBJECTIVE: We aim to develop and validate an interpretable machine-learning model that can provide critical information for the clinical treatment of critically ill patients with acute myocardial infarction (AMI).
Machine learning approach on plasma proteomics identifies signatures associated with obesity in the KORA FF4 cohort.
Diabetes, obesity & metabolism
Feb 27, 2025
AIMS: This study investigated the role of plasma proteins in obesity to identify predictive biomarkers and explore underlying biological mechanisms.
Contribution of Structure Learning Algorithms in Social Epidemiology: Application to Real-World Data.
International journal of environmental research and public health
Feb 27, 2025
Epidemiologists often handle large datasets with numerous variables and are currently seeing a growing wealth of techniques for data analysis, such as machine learning. Critical aspects involve addressing causality, often based on observational data,...
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)...
Predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients based on ultrasound longitudinal temporal depth network fusion model.
Breast cancer research : BCR
Feb 27, 2025
OBJECTIVE: The aim of this study was to develop and validate a deep learning radiomics (DLR) model based on longitudinal ultrasound data and clinical features to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breas...
Prediction of sarcopenia at different time intervals: an interpretable machine learning analysis of modifiable factors.
BMC geriatrics
Feb 27, 2025
OBJECTIVES: This study aims to develop sarcopenia risk prediction models for Chinese older adults at different time intervals and to identify and compare modifiable factors contributing to sarcopenia development.
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