[HTML][HTML] Prediction of coronary heart disease based on combined reinforcement multitask progressive time-series networks

W Li, M Zuo, H Zhao, Q Xu, D Chen - Methods, 2022 - Elsevier
Coronary heart disease is the first killer of human health. At present, the most widely used
approach of coronary heart disease diagnosis is coronary angiography, a surgery that could …

Deep machine learning application to the detection of preclinical neurodegenerative diseases of aging

MJ Summers, T Madl, AE Vercelli… - … Scientific Journal on …, 2017 - digitcult.lim.di.unimi.it
Abstract [eng] Artificial intelligence (AI) deep learning protocols offer solutions to complex
data processing and analysis. Increasingly these solutions are being applied in the …

Gated temporal convolutional neural network and expert features for diagnosing and explaining physiological time series: a case study on heart rates

S Hong, C Wang, Z Fu - Computer Methods and Programs in Biomedicine, 2021 - Elsevier
Abstract Background and Objective: Physiological time series are common data sources in
many health applications. Mining data from physiological time series is crucial for promoting …

Coronary heart disease prediction based on combined reinforcement multitask progressive networks

W Li, D Chen, J Le - 2020 IEEE International Conference on …, 2020 - ieeexplore.ieee.org
Coronary heart disease is the first killer of human health. At present, the common way of
coronary heart disease diagnosis is coronary angiography. This method is a kind of surgery …

[PDF][PDF] Assessing the physical capabilities of sportsman

J De Clerck - libstore.ugent.be
Method The goal of this master thesis is to use machine learning to develop a digital
personal coach for sport activities. 2 subgoals have been isolated: A model capable of …

Performance Evaluation of Deep Neural Network (DNN) Based on HRV Parameters for Judgment of Risk Factors for Coronary Artery Disease

SJ Park, SY Choi, YM Kim - Journal of Biomedical Engineering …, 2019 - koreascience.kr
The purpose of this study was to evaluate the performance of deep neural network model in
order to determine whether there is a risk factor for coronary artery disease based on the …