AIMC Topic: Humans

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A Myocardial Segmentation Method Based on Adversarial Learning.

BioMed research international
Congenital heart defects (CHD) are structural imperfections of the heart or large blood vessels that are detected around birth and their symptoms vary wildly, with mild case patients having no obvious symptoms and serious cases being potentially life...

Two-Dimensional Stockwell Transform and Deep Convolutional Neural Network for Multi-Class Diagnosis of Pathological Brain.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Since the brain lesion detection and classification is a vital diagnosis task, in this paper, the problem of brain magnetic resonance imaging (MRI) classification is investigated. Recent advantages in machine learning and deep learning allows the res...

CTNN: A Convolutional Tensor-Train Neural Network for Multi-Task Brainprint Recognition.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Brainprint is a new type of biometric in the form of EEG, directly linking to intrinsic identity. Currently, most methods for brainprint recognition are based on traditional machine learning and only focus on a single brain cognition task. Due to the...

Peri-operative blood management of Jehovah's Witnesses undergoing cytoreductive surgery for advanced ovarian cancer.

Blood transfusion = Trasfusione del sangue
BACKGROUND: The aim of this study was to evaluate the efficacy and feasibility of a peri-operative bloodless medicine and surgery (BMS) protocol in reducing severe post-operative anaemia (haemoglobin [Hb] <7 g/dL) in Jehovah's Witnesses undergoing cy...

Using Deep Learning to Emulate the Use of an External Contrast Agent in Cardiovascular 4D Flow MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Although contrast agents would be beneficial, they are seldom used in four-dimensional (4D) flow magnetic resonance imaging (MRI) due to potential side effects and contraindications.

Contrast agent dose reduction in computed tomography with deep learning using a conditional generative adversarial network.

European radiology
OBJECTIVES: To reduce the dose of intravenous iodine-based contrast media (ICM) in CT through virtual contrast-enhanced images using generative adversarial networks.

Deep neural networks with promising diagnostic accuracy for the classification of atypical femoral fractures.

Acta orthopaedica
Background and purpose - A correct diagnosis is essential for the appropriate treatment of patients with atypical femoral fractures (AFFs). The diagnostic accuracy of radiographs with standard radiology reports is very poor. We derived a diagnostic a...

Development and Validation of a Deep Learning Based Diabetes Prediction System Using a Nationwide Population-Based Cohort.

Diabetes & metabolism journal
BACKGROUND: Previously developed prediction models for type 2 diabetes mellitus (T2DM) have limited performance. We developed a deep learning (DL) based model using a cohort representative of the Korean population.

Artificial neural network and logistic regression modelling to characterize COVID-19 infected patients in local areas of Iran.

Biomedical journal
BACKGROUND: COVID-19 is an infectious disease that started spreading globally at the end of 2019. Due to differences in patient characteristics and symptoms in different regions, in this research, a comparative study was performed on COVID-19 patient...