AIMC Topic: Middle Aged

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Exploring the influence of nasal vestibule structure on nasal obstruction using CFD and Machine Learning method.

Medical engineering & physics
Motivated by clinical findings about the nasal vestibule, this study analyzes the aerodynamic characteristics of the nasal vestibule and attempt to determine anatomical features which have a large influence on airflow through a combination of Computa...

Detection and quantification of breast arterial calcifications on mammograms: a deep learning approach.

European radiology
OBJECTIVE: Breast arterial calcifications (BAC) are a sex-specific cardiovascular disease biomarker that might improve cardiovascular risk stratification in women. We implemented a deep convolutional neural network for automatic BAC detection and qua...

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.

Nature medicine
Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods to clinical data from 6 million patients (24,000 p...

High-Speed On-Site Deep Learning-Based FFR-CT Algorithm: Evaluation Using Invasive Angiography as the Reference Standard.

AJR. American journal of roentgenology
Estimation of fractional flow reserve from coronary CTA (FFR-CT) is an established method of assessing the hemodynamic significance of coronary lesions. However, clinical implementation has progressed slowly, partly because of off-site data transfer...

A machine learning approach for the diagnosis of obstructive sleep apnoea using oximetry, demographic and anthropometric data.

Singapore medical journal
INTRODUCTION: Obstructive sleep apnoea (OSA) is a serious but underdiagnosed condition. Demand for the gold standard diagnostic polysomnogram (PSG) far exceeds its availability. More efficient diagnostic methods are needed, even in tertiary settings....

A deep learning-based application for COVID-19 diagnosis on CT: The Imaging COVID-19 AI initiative.

PloS one
BACKGROUND: Recently, artificial intelligence (AI)-based applications for chest imaging have emerged as potential tools to assist clinicians in the diagnosis and management of patients with coronavirus disease 2019 (COVID-19).

Deep learning segmentation results in precise delineation of the putamen in multiple system atrophy.

European radiology
OBJECTIVES: The precise segmentation of atrophic structures remains challenging in neurodegenerative diseases. We determined the performance of a Deep Neural Patchwork (DNP) in comparison to established segmentation algorithms regarding the ability t...

Artificial intelligence using a deep learning versus expert computed tomography human reading in calcium score and coronary artery calcium data and reporting system classification.

Coronary artery disease
BACKGROUND: Artificial intelligence (AI) applied to cardiac imaging may provide improved processing, reading precision and advantages of automation. Coronary artery calcium (CAC) score testing is a standard stratification tool that is rapid and highl...

Development and Validation of a Joint Attention-Based Deep Learning System for Detection and Symptom Severity Assessment of Autism Spectrum Disorder.

JAMA network open
IMPORTANCE: Joint attention, composed of complex behaviors, is an early-emerging social function that is deficient in children with autism spectrum disorder (ASD). Currently, no methods are available for objectively quantifying joint attention.

Machine Learning-Based Prognostic Model for Patients After Lung Transplantation.

JAMA network open
IMPORTANCE: Although numerous prognostic factors have been found for patients after lung transplantation (LTx) over the years, an accurate prognostic tool for LTx recipients remains unavailable.