AIMC Topic: Middle Aged
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Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations: a real-world clinical analysis.
European radiology
Nov 29, 2024
PURPOSE: The purpose of this study is to estimate the extent to which the implementation of deep learning reconstruction (DLR) may reduce the risk of radiation-induced cancer from CT examinations, utilizing real-world clinical data.
Development and Validation of a Machine Learning Radiomics Model based on Multiparametric MRI for Predicting Progesterone Receptor Expression in Meningioma: A Multicenter Study.
Academic radiology
Nov 29, 2024
RATIONALE AND OBJECTIVES: This study aimed to develop and validate a machine learning-based prediction model for preoperatively predicting progesterone receptor (PR) expression in meningioma patients using multiparametric magnetic resonance imaging (...
Attitudes of nurses toward artificial intelligence: A multicenter comparison.
Work (Reading, Mass.)
Nov 29, 2024
BackgroundArtificial intelligence (AI) is transforming medical practices with rapidly developing technologies and the innovative solutions it provides. In order for this transformation to be successfully integrated into healthcare services, healthcar...
Data - Knowledge driven machine learning model for cancer pain medication decisions.
International journal of medical informatics
Nov 29, 2024
BACKGROUND: Cancer pain is one of the most common symptoms in cancer patients, and drug decision-making in cancer pain management remains challenges. This study aims to develop machine learning models using real-world clinical data and prior knowledg...
A randomized controlled trial on evaluating clinician-supervised generative AI for decision support.
International journal of medical informatics
Nov 29, 2024
BACKGROUND: The integration of generative artificial intelligence (AI) as clinical decision support systems (CDSS) into telemedicine presents a significant opportunity to enhance clinical outcomes, yet its application remains underexplored.
Interpretable time-series neural turing machine for prognostic prediction of patients with type 2 diabetes in physician-pharmacist collaborative clinics.
International journal of medical informatics
Nov 29, 2024
BACKGROUND: Type 2 diabetes (T2D) has become a serious health threat globally. However, the existing approaches for diabetes prediction mainly had difficulty in addressing multiple time-series features. This study aims to provide an adjunctive tool f...
MicroRNA signature for early prediction of knee osteoarthritis structural progression using integrated machine and deep learning approaches.
Osteoarthritis and cartilage
Nov 29, 2024
OBJECTIVE: Conventional methodologies are ineffective in predicting the rapid progression of knee osteoarthritis (OA). MicroRNAs (miRNAs) show promise as biomarkers for patient stratification. We aimed to develop a miRNA prognosis model for identifyi...
Assessment of clinical feasibility:offline adaptive radiotherapy for lung cancer utilizing kV iCBCT and UNet++ based deep learning model.
Journal of applied clinical medical physics
Nov 29, 2024
BACKGROUND: Lung cancer poses a significant global health challenge. Adaptive radiotherapy (ART) addresses uncertainties due to lung tumor dynamics. We aimed to investigate a comprehensively and systematically validated offline ART regimen with high ...
Left Atrial Wall Thickness Measured by a Machine Learning Method Predicts AF Recurrence After Pulmonary Vein Isolation.
Journal of cardiovascular electrophysiology
Nov 29, 2024
BACKGROUND: Left atrial (LA) remodeling plays a significant role in the progression of atrial fibrillation (AF). Although LA wall thickness (LAWT) has emerged as an indicator of structural remodeling, its impact on AF outcomes remains unclear. We aim...
Humans
Machine Learning
Retrospective Studies
Female
Atrial Function, Left
Pulmonary Veins
Atrial Remodeling
Heart Atria
Risk Assessment
Risk Factors
Predictive Value of Tests
Heart Rate
Aged
Registries
Catheter Ablation
Time Factors
Male
Fibrosis
Recurrence
Treatment Outcome
Middle Aged
Atrial Fibrillation
Action Potentials
An ECG-based machine-learning approach for mortality risk assessment in a large European population.
Journal of electrocardiology
Nov 29, 2024
AIMS: Through a simple machine learning approach, we aimed to assess the risk of all-cause mortality after 5 years in a European population, based on electrocardiogram (ECG) parameters, age, and sex.
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