AIMC Topic: Aged

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Automated annotation of virtual dual stains to generate convolutional neural network for detecting cancer metastases in H&E-stained lymph nodes.

Pathology, research and practice
CONTEXT: Staging cancer patients is crucial and requires analyzing all removed lymph nodes microscopically for metastasis. For this pivotal task, convolutional neural networks (CNN) can reduce workload and improve diagnostic accuracy.

A magnetic resonance imaging (MRI)-based deep learning radiomics model predicts recurrence-free survival in lung cancer patients after surgical resection of brain metastases.

Clinical radiology
AIM: To develop and validate a magnetic resonance imaging (MRI)-based deep learning radiomics model (DLRM) to predict recurrence-free survival (RFS) in lung cancer patients after surgical resection of brain metastases (BrMs).

Diagnosis of carpal tunnel syndrome using deep learning with comparative guidance.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: This study aims to develop a deep learning model for a robust diagnosis of Carpal Tunnel Syndrome (CTS) based on comparative classification leveraging the ultrasound images of the thenar and hypothenar muscles.

AI-based prediction of left bundle branch block risk post-TAVI using pre-implantation clinical parameters.

Future cardiology
BACKGROUND AND AIMS: Transcatheter Aortic Valve Implantation (TAVI) has revolutionized the treatment of severe aortic stenosis. Although its clinical efficacy is well established, the development of new-onset left bundle branch block (LBBB) following...

Metabolic Dysfunction-Associated Steatotic Liver Disease Is Associated With Accelerated Brain Ageing: A Population-Based Study.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is linked to cognitive decline and dementia risk. We aimed to investigate the association between MASLD and brain ageing and explore the role of low-grade inflammation.

Multidimensional Feature Analysis of Meniere's Disease and Vestibular Migraine: Insights from Machine Learning and Vestibular Testing.

Journal of the Association for Research in Otolaryngology : JARO
OBJECTIVE: Differentiating between Meniere's disease (MD) and vestibular migraine (VM) is challenging due to overlapping symptoms and limited diagnostic tools. Traditional statistical methods often rely on physician judgment and struggle with complex...

Predicting Severe Postoperative Complications after CRS-HIPEC: An Externally Validated Machine-Learning Tool.

World journal of surgery
INTRODUCTION: Current decision support tools designed to predict postoperative complications, following cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC), are limited by small sample sizes and lack of external validatio...

Leveraging GPT-4 enables patient comprehension of radiology reports.

European journal of radiology
OBJECTIVE: To assess the feasibility of using GPT-4 to simplify radiology reports into B1-level Dutch for enhanced patient comprehension.

Development of a deep neural network model for ultra-early neurological deterioration in ischemic stroke and analysis of associated risk factors.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: In this study, we established a deep neural network (DNN)-based predictive model, aiming to provide a basis for improving the treatment prognosis of early neurological deterioration (END) in patients with ultra-early ischemic stroke after...