AIMC Topic: Aged, 80 and over
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Machine learning-based model to predict composite thromboembolic events among Chinese elderly patients with atrial fibrillation.
BMC cardiovascular disorders
Aug 13, 2024
OBJECTIVE: Accurate prediction of survival prognosis is helpful to guide clinical decision-making. The aim of this study was to develop a model using machine learning techniques to predict the occurrence of composite thromboembolic events (CTEs) in e...
Incremental Value of Multidomain Risk Factors for Dementia Prediction: A Machine Learning Approach.
The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
Aug 10, 2024
OBJECTIVE: The current evidence regarding how different predictor domains contributes to predicting incident dementia remains unclear. This study aims to assess the incremental value of five predictor domains when added to a simple dementia risk pred...
Leveraging feature selection for enhanced fall risk prediction in elderly using gait analysis.
Medical & biological engineering & computing
Aug 10, 2024
There is no effective fall risk screening tool for the elderly that can be integrated into clinical practice. Developing a system that can be easily used in primary care services is a current need. Current studies focus on the use of multiple sensors...
Joint use of population pharmacokinetics and machine learning for prediction of valproic acid plasma concentration in elderly epileptic patients.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Aug 10, 2024
BACKGROUND: Valproic acid (VPA) is a commonly used broad-spectrum antiepileptic drug. For elderly epileptic patients, VPA plasma concentrations have a considerable variation. We aim to establish a prediction model via a combination of machine learnin...
Application of machine learning to predict in-hospital mortality after transcatheter mitral valve repair.
Surgery
Aug 9, 2024
INTRODUCTION: Transcatheter mitral valve repair offers a minimally invasive treatment option for patients at high risk for traditional open repair. We sought to develop dynamic machine-learning risk prediction models for in-hospital mortality after t...
Accuracy and time efficiency of a novel deep learning algorithm for Intracranial Hemorrhage detection in CT Scans.
La Radiologia medica
Aug 9, 2024
PURPOSE: To evaluate a deep learning-based pipeline using a Dense-UNet architecture for the assessment of acute intracranial hemorrhage (ICH) on non-contrast computed tomography (NCCT) head scans after traumatic brain injury (TBI).
Clinical application of convolutional neural network lung nodule detection software: An Australian quaternary hospital experience.
Journal of medical imaging and radiation oncology
Aug 9, 2024
INTRODUCTION: Early-stage lung cancer diagnosis through detection of nodules on computed tomography (CT) remains integral to patient survivorship, promoting national screening programmes and diagnostic tools using artificial intelligence (AI) convolu...
Significance of plasma p-tau217 in predicting long-term dementia risk in older community residents: Insights from machine learning approaches.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Aug 8, 2024
INTRODUCTION: Whether plasma biomarkers play roles in predicting incident dementia among the general population is worth exploring.
Unbiased identification of risk factors for invasive Escherichia coli disease using machine learning.
BMC infectious diseases
Aug 8, 2024
BACKGROUND: Invasive Escherichia coli disease (IED), also known as invasive extraintestinal pathogenic E. coli disease, is a leading cause of sepsis and bacteremia in older adults that can result in hospitalization and sometimes death and is frequent...
Measurable residual disease (MRD) dynamics in multiple myeloma and the influence of clonal diversity analyzed by artificial intelligence.
Blood cancer journal
Aug 7, 2024
Minimal residual disease (MRD) assessment is a known surrogate marker for survival in multiple myeloma (MM). Here, we present a single institution's experience assessing MRD by NGS of Ig genes and the long-term impact of depth of response as well as ...
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