AIMC Topic: Middle Aged

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Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank.

BMC medicine
BACKGROUND: Currently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, in which 10% 10-year CVD risk indicates clinical intervention. However, this benchmark has limited efficacy in clinical practice a...

Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.

Zeitschrift fur medizinische Physik
INTRODUCTION: Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strategy. To assess neuroinflammation in vivo, translocator protein PET (TSPO PET) can be used. However, t...

A deep learning model incorporating spatial and temporal information successfully detects visual field worsening using a consensus based approach.

Scientific reports
Glaucoma is a leading cause of irreversible blindness, and its worsening is most often monitored with visual field (VF) testing. Deep learning models (DLM) may help identify VF worsening consistently and reproducibly. In this study, we developed and ...

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review.

Journal of medical Internet research
BACKGROUND: Anxiety and depression are the most common mental disorders worldwide. Owing to the lack of psychiatrists around the world, the incorporation of artificial intelligence (AI) into wearable devices (wearable AI) has been exploited to provid...

Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI).

Reliability of respiratory-gated real-time two-dimensional cine incorporating deep learning reconstruction for the assessment of ventricular function in an adult population.

The international journal of cardiovascular imaging
This study aimed to assess the image quality and accuracy of respiratory-gated real-time two-dimensional (2D) cine incorporating deep learning reconstruction (DLR) for the quantification of biventricular volumes and function compared with those of th...

Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.

Radiology
Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome undergo additional testing to exclude acute coronary syndrome (ACS), pulmonary embolism (PE), or aortic dissection (AD), often yielding negative resu...

Age-specific risk factors for the prediction of obesity using a machine learning approach.

Frontiers in public health
Machine Learning is a powerful tool to discover hidden information and relationships in various data-driven research fields. Obesity is an extremely complex topic, involving biological, physiological, psychological, and environmental factors. One suc...

A machine-learning algorithm for predicting brain age using Rey-Osterrieth complex figure tests of healthy participants.

Applied neuropsychology. Adult
OBJECTIVE: Neuropsychologists widely use the Rey-Osterrieth complex figure test (RCFT) as part of neuropsychological test batteries to evaluate cognitive function and assess constructional ability, with age being the most significant factor. Our stud...

Retzius-sparing robot-assisted radical prostatectomy in a medium size oncological center holds adequate oncological and functional outcomes.

Journal of robotic surgery
Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) has emerged as a surgical option for patients with prostatic cancer in high-volume centers. The objective is to assess oncological and functional outcomes when implementing RS-RARP in a m...