Congestive Heart Failure

Use of Deep-Learning Assisted Assessment of Cardiac Parameters in Zebrafish to Discover Cyanidin Chloride as a Novel Keap1 Inhibitor Against Doxorubicin-Induced Cardiotoxicity.

Doxorubicin-induced cardiomyopathy (DIC) brings tough clinical challenges as well as continued demand in developing agents for adjuvant cardioprotective therapies. Here, a zebrafish phenotypic screening with deep-learning assisted multiplex cardiac functional analysis using motion videos of larval hearts is established. Through training the model on a dataset of 2125 labeled ventricular images, ZV...

Automatic Detection of Dyspnea in Real Human-Robot Interaction Scenarios.

A respiratory distress estimation technique for telephony previously proposed by the authors is adapted and evaluated in real static and dynamic HRI scenarios. The system is evaluated with a telephone dataset re-recorded using the robotic platform designed and implemented for this study. In addition, the original telephone training data are modified using an environmental model that incorporates n...

Automated estimation of mitral annular plane systolic excursion by artificial intelligence from 3D ultrasound recordings.

Perioperative monitoring of cardiac function is beneficial for early detection of cardiovascular complications. The standard of care for cardiac monit...

Bilateral subgaleal hematoma after a robot-assisted radical prostatectomy: an uncommon complication.

Robot-assisted radical prostatectomy is a relatively recent technique. Its advantages include less invasiveness and better pain management, but has sp...

Safety evaluation and effects of cascara pulp Gayo Arabica coffee cream as anti-photoaging in animal model.

Prolonged sunlight and ultraviolet (UV) exposure causes premature skin aging called photoaging and coffee-derived topical antioxidants may help to red...

Risk Stratification in Hypertrophic Cardiomyopathy: Leveraging Artificial Intelligence to Provide Guidance in the Future.

A Deep Learning Approach to Using Wearable Seismocardiography (SCG) for Diagnosing Aortic Valve Stenosis and Predicting Aortic Hemodynamics Obtained by 4D Flow MRI.

In this paper, we explored the use of deep learning for the prediction of aortic flow metrics obtained using 4-dimensional (4D) flow magnetic resonanc...

Neural network for autonomous segmentation and volumetric assessment of clot and edema in acute and subacute intracerebral hemorrhages.

INTRODUCTION: Minimally-invasive surgical techniques for intracerebral hemorrhage (ICH) evacuation use imaging to guide the suction, lysing and/or dra...

Classification of electrocardiogram signals using deep learning based on genetic algorithm feature extraction.

Arrhythmias using electrocardiogram (ECG) signal is important in medical and computer research due to the timely diagnosis of dangerous cardiac condit...

NT-proBNP in patients presenting with myocardial infarction and non-obstructive coronary arteries without left ventricular systolic dysfunction.

BACKGROUND: Myocardial infarction and non-obstructive coronary arteries (MINOCA) affects 1 in 9 patients with acute coronary syndrome and has no evide...

Optical Coherence Tomography Image Classification Using Hybrid Deep Learning and Ant Colony Optimization.

Optical coherence tomography (OCT) is widely used to detect and classify retinal diseases. However, OCT-image-based manual detection by ophthalmologis...

Elastic Deformation of Optical Coherence Tomography Images of Diabetic Macular Edema for Deep-Learning Models Training: How Far to Go?

UNLABELLED: - Objective: To explore the clinical validity of elastic deformation of optical coherence tomography (OCT) images for data augmentation in...

A Novel ECG-Based Deep Learning Algorithm to Predict Cardiomyopathy in Patients With Premature Ventricular Complexes.

BACKGROUND: Premature ventricular complexes (PVCs) are prevalent and, although often benign, they may lead to PVC-induced cardiomyopathy. We created a...

Auto-Segmentation and Classification of Glioma Tumors with the Goals of Treatment Response Assessment Using Deep Learning Based on Magnetic Resonance Imaging.

Glioma is the most common primary intracranial neoplasm in adults. Radiotherapy is a treatment approach in glioma patients, and Magnetic Resonance Ima...

Deep Learning for Discrimination of Hypertrophic Cardiomyopathy and Hypertensive Heart Disease on MRI Native T1 Maps.

BACKGROUND: Native T1 and radiomics were used for hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD) differentiation previously. T...

Hybrid Recommender System for Mental Illness Detection in Social Media Using Deep Learning Techniques.

Recommender systems are chiefly renowned for their applicability in e-commerce sites and social media. For system optimization, this work introduces a...

Fully automatic estimation of global left ventricular systolic function using deep learning in transoesophageal echocardiography.

AIMS: To improve monitoring of cardiac function during major surgery and intensive care, we have developed a method for fully automatic estimation of ...

APPRAISE-HRI: AN ARTIFICIAL INTELLIGENCE ALGORITHM FOR TRIAGE OF HEMORRHAGE CASUALTIES.

Background: Hemorrhage remains the leading cause of death on the battlefield. This study aims to assess the ability of an artificial intelligence tria...

Deep Learning-Based Non-Contact IPPG Signal Blood Pressure Measurement Research.

In this paper, a multi-stage deep learning blood pressure prediction model based on imaging photoplethysmography (IPPG) signals is proposed to achieve...

Shortwave infrared diffuse optical wearable probe for quantification of water and lipid content in emulsion phantoms using deep learning.

SIGNIFICANCE: The shortwave infrared (SWIR, to 2000 nm) holds promise for label-free measurements of water and lipid content in thick tissue, owed to...