AIMC Topic: Middle Aged

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Radical cystectomy in women: Impact of the robot-assisted versus open approach on surgical outcomes.

Urologic oncology
OBJECTIVES: To perform a comparison of complications following open versus robot-assisted radical cystectomy (RC) among women who undergo the procedure. Studies comparing robotic to open RC have been mixed without a clear delineation of which patient...

Multi-label classification of retinal lesions in diabetic retinopathy for automatic analysis of fundus fluorescein angiography based on deep learning.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To automatically detect and classify the lesions of diabetic retinopathy (DR) in fundus fluorescein angiography (FFA) images using deep learning algorithm through comparing 3 convolutional neural networks (CNNs).

Convolutional neural network-automated hepatobiliary phase adequacy evaluation may optimize examination time.

European journal of radiology
PURPOSE: To develop and evaluate the performance of a fully-automated convolutional neural network (CNN)-based algorithm to evaluate hepatobiliary phase (HBP) adequacy of gadoxetate disodium (EOB)-enhanced MRI. Secondarily, we explored the potential ...

Prediction of progression from pre-diabetes to diabetes: Development and validation of a machine learning model.

Diabetes/metabolism research and reviews
AIMS: Identification, a priori, of those at high risk of progression from pre-diabetes to diabetes may enable targeted delivery of interventional programmes while avoiding the burden of prevention and treatment in those at low risk. We studied whethe...

Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India.

Scientific reports
In general, chest radiographs (CXR) have high sensitivity and moderate specificity for active pulmonary tuberculosis (PTB) screening when interpreted by human readers. However, they are challenging to scale due to hardware costs and the dearth of pro...

Validation of deep-learning image reconstruction for coronary computed tomography angiography: Impact on noise, image quality and diagnostic accuracy.

Journal of cardiovascular computed tomography
BACKGROUND: Advances in image reconstruction are necessary to decrease radiation exposure from coronary CT angiography (CCTA) further, but iterative reconstruction has been shown to degrade image quality at high levels. Deep-learning image reconstruc...

Long short-term memory artificial neural network model for prediction of prostate cancer survival outcomes according to initial treatment strategy: development of an online decision-making support system.

World journal of urology
PURPOSE: The delivery of precision medicine is a primary objective for both clinical and translational investigators. Patients with newly diagnosed prostate cancer (PCa) face the challenge of deciding among multiple initial treatment modalities. The ...

Machine-learning facilitates selection of a novel diagnostic panel of metabolites for the detection of heart failure.

Scientific reports
The metabolic derangement is common in heart failure with reduced ejection fraction (HFrEF). The aim of the study was to check feasibility of the combined approach of untargeted metabolomics and machine learning to create a simple and potentially cli...

Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals.

PloS one
Several European countries have established criteria for prioritising initiation of treatment in patients infected with the hepatitis C virus (HCV) by grouping patients according to clinical characteristics. Based on neural network techniques, our ob...