AIMC Topic: Heart Diseases
Clear Filters Showing 181 to 190 of 198 articles
Local large language models for privacy-preserving accelerated review of historic echocardiogram reports.
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVES: The study developed framework that leverages an open-source Large Language Model (LLM) to enable clinicians to ask plain-language questions about a patient's entire echocardiogram report history. This approach is intended to streamline th...
AI-Supported Echocardiography for the Detection of Heart Diseases - A Scoping Review.
Studies in health technology and informatics
Aug 30, 2024
INTRODUCTION: Cardiovascular diseases are a leading cause of mortality worldwide, highlighting the urgent need for accurate and efficient diagnostic tools. Echocardiography, a non-invasive imaging technique, plays a central role in the diagnosis of h...
Learning Physiological Mechanisms that Predict Adverse Cardiovascular Events in Intensive Care Patients with Chronic Heart Disease.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Chronic heart disease is a burdensome, complex, and fatal condition. Learning the mechanisms driving the development of heart disease is key to early risk assessment and intervention. However, many current machine learning approaches lack sufficient ...
Untrained Network for Super-resolution for Non-contrast-enhanced Wholeheart MRI Acquired using Cardiac-triggered REACT (SRNN-REACT).
Current medical imaging
Jan 1, 2024
BACKGROUND: Three-dimensional (3D) whole-heart magnetic resonance imaging (MRI) is an excellent tool to check the heart anatomy of patients with congenital and acquired heart disease. However, most 3D whole-heart MRI acquisitions take a long time to ...
Deep Time Growing Neural Network vs Convolutional Neural Network for Intelligent Phonocardiography.
Studies in health technology and informatics
Jun 29, 2022
This paper explores the capabilities of a sophisticated deep learning method, named Deep Time Growing Neural Network (DTGNN), and compares its possibilities against a generally well-known method, Convolutional Neural network (CNN). The comparison is ...
[Screening biomarkers for hypertensive heart disease: Analysis based on data from 7 medical institutions].
Zhongguo ying yong sheng li xue za zhi = Zhongguo yingyong shenglixue zazhi = Chinese journal of applied physiology
Mar 1, 2021
To screen the influencing factors of hypertensive heart disease (HHD), establish the predictive model of HHD, and provide early warning for the occurrence of HHD. Select the patients diagnosed as hypertensive heart disease or hypertensionfrom Janua...
Efficient heart disease prediction-based on optimal feature selection using DFCSS and classification by improved Elman-SFO.
IET systems biology
Dec 1, 2020
Prediction of cardiovascular disease (CVD) is a critical challenge in the area of clinical data analysis. In this study, an efficient heart disease prediction is developed based on optimal feature selection. Initially, the data pre-processing process...
Artificial Intelligence in Cardiology: Present and Future.
Mayo Clinic proceedings
May 1, 2020
Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE da...
Artificial Intelligence Pertaining to Cardiothoracic Imaging and Patient Care: Beyond Image Interpretation.
Journal of thoracic imaging
May 1, 2020
Artificial intelligence (AI) is a broad field of computational science that includes many subsets. Today the most widely used subset in medical imaging is machine learning (ML). Many articles have focused on the use of ML for pattern recognition to d...
Predicting Future Cardiovascular Events in Patients With Peripheral Artery Disease Using Electronic Health Record Data.
Circulation. Cardiovascular quality and outcomes
Mar 1, 2019
BACKGROUND: Patients with peripheral artery disease (PAD) are at risk of major adverse cardiac and cerebrovascular events. There are no readily available risk scores that can accurately identify which patients are most likely to sustain an event, mak...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31037
- Neural Networks, Computer 29719
- Algorithms 26832
- Deep Learning 26346
- Artificial Intelligence 24295
- Robotics 13311
- Image Processing, Computer-Assisted 9521
- Retrospective Studies 9111
- Magnetic Resonance Imaging 6181
- Reproducibility of Results 5592
- Tomography, X-Ray Computed 4771
- Support Vector Machine 4686
- Computational Biology 4237
- Brain 4050
- Computer Simulation 3881
Recent Journals
- Scientific reports 5949
- Sensors (Basel, Switzerland) 4794
- PloS one 4015
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1859
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1130
- Journal of chemical information and modeling 998
- Nature communications 944
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 826