Robust and accurate modeling approaches for migraine per-patient prediction from ambulatory data

J Pagán, M Irene De Orbe, A Gago, M Sobrado… - Sensors, 2015 - mdpi.com
Migraine is one of the most wide-spread neurological disorders, and its medical treatment
represents a high percentage of the costs of health systems. In some patients, characteristic …

Deep-Learning-Based Strong Ground Motion Signal Prediction in Real Time

M AlHamaydeh, S Tellab, U Tariq - Buildings, 2024 - mdpi.com
Processing ground motion signals at early stages can be advantageous for issuing public
warnings, deploying first-responder teams, and other time-sensitive measures. Multiple …

[HTML][HTML] Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases

J Pagán, JL Risco-Martín, JM Moya, JL Ayala - Journal of biomedical …, 2016 - Elsevier
Prediction of symptomatic crises in chronic diseases allows to take decisions before the
symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of …

System for indirect temperature measurement in annealing process

M Durdán, A Mojžišová, M Laciak, J Kačur - Measurement, 2014 - Elsevier
Metal heating represents one of most important technology operations within technology
processes of metallurgy and engineering plants, influencing production with regard to …

Применение нейросетей и алгоритмов машинного обучения с целью диагностики сердечно-сосудистых заболеваний на основе сигналов СКГ

НС Коннова, ВЮ Хаперская - Биомедицинская радиоэлектроника, 2020 - elibrary.ru
Постановка проблемы. Заболевания сердечно-сосудистой системы являются основной
причиной смертности по всему миру. Для того, чтобы уменьшить смертность и …

[PDF][PDF] Suitability of neural network for di

U Sharma - Research Journal of Computer and Informa, 2017 - isca.me
In this study, suitability and appropriateness of neural from a comprehensive literature
review. Wherein, rese different various architecture of Artificial Neural Netw Faction (RBF) …

E-mail: nkonnova@ bmstu. ru V. Yu. Khaperskaya–Post-graduate Student, Bauman Moscow State Technical University E-mail: lynx. lg@ gmail. com

NS Konnova - radiotec.ru
Application of machine learning algorithms and neural networks for SCG signal classification |
Publishing house Radiotekhnika Home About us News For authors Payment and delivery …

Prediction of ECG Signals Using Feedforward Neural Networks

BA Kwembe, A Mohammed, JG Bashayi… - International Journal of …, 2019 - ijciar.com
The Electrocardiogram (ECG) signal could be modelled or analysed using time series
prediction methods. This study considered neural networks models trained with ECG data …

[引用][C] Measurement and analysis possibilities of pulse wave signals

S Borik, I Cap - Advances in Electrical and Electronic Engineering, 2013

[引用][C] Machine Learning Based Real-Time Earthquake Signal Prediction

S Tellab - 2020