[HTML][HTML] EpilepsyNet: Novel automated detection of epilepsy using transformer model with EEG signals from 121 patient population

OS Lih, V Jahmunah, EE Palmer, PD Barua… - Computers in Biology …, 2023 - Elsevier
Background Epilepsy is one of the most common neurological conditions globally, and the
fourth most common in the United States. Recurrent non-provoked seizures characterize it …

Telemedicine and epilepsy care

B Lavin, CL Gray, M Brodie - Neurologic Clinics, 2022 - neurologic.theclinics.com
Telehealth, often used interchangeably with telemedicine, involves the use of
telecommunication technology for the exchange of medical information from one location to …

[HTML][HTML] ECG diagnostic support system (EDSS): A deep learning neural network based classification system for detecting ECG abnormal rhythms from a low-powered …

EB Panganiban, AC Paglinawan, WY Chung… - Sensing and Bio …, 2021 - Elsevier
The latest developments in deep learning have made it possible to implement automated,
advanced extraction of several things' features and classifications. Deep learning methods …

[HTML][HTML] A Robust Automatic Epilepsy Seizure Detection Algorithm Based on Interpretable Features and Machine Learning

S Liu, Y Zhou, X Yang, X Wang, J Yin - Electronics, 2024 - mdpi.com
Epilepsy, as a serious neurological disorder, can be detected by analyzing the brain signals
produced by neurons. Electroencephalogram (EEG) signals are the most important data …

Low‐cost portable EEG device for bridging the diagnostic gap in resource‐limited areas

S Armand Larsen, L Klok, W Lehn‐Schiøler… - Epileptic …, 2024 - Wiley Online Library
Objective To develop a low‐cost portable EEG system, with real‐time automated guidance,
for application in resource‐limited areas, to bridge the diagnostic and treatment gap …

Digital transformation in epilepsy diagnosis using raw images and transfer learning in electroencephalograms

MS Muñoz, CES Torres, R Salazar-Cabrera, DM López… - Sustainability, 2022 - mdpi.com
Epilepsy diagnosis is a medical care process that requires considerable transformation,
mainly in developed countries, to provide efficient and effective care services taking into …

Exploring and predicting mortality among patients with end-stage liver disease without cancer: a machine learning approach

CS Yu, YD Chen, SS Chang, JH Tang… - European Journal of …, 2021 - journals.lww.com
Objective End-stage liver disease is a global public health problem with a high mortality rate.
Early identification of people at risk of poor prognosis is fundamental for decision-making in …

Applications of medical digital technologies for noncommunicable diseases for follow-up during the COVID-19 pandemic

ESE Hussein, AM Al-Shenqiti… - International Journal of …, 2022 - mdpi.com
Background: Noncommunicable chronic diseases (NCDs) are multifaceted, and the health
implications of the COVID-19 pandemic are far-reaching, especially for NCDs. Physical …

Research on Intelligent collar animal husbandry health diagnosis service platform based on Cloud Computing

C Jia, F Dong - 2022 World Automation Congress (WAC), 2022 - ieeexplore.ieee.org
The health status of livestock is closely related to the economic benefits of pastures. The
traditional health monitoring of livestock still depends on human judgment. With the …

An overview of artificial intelligence and blockchain technology in telehealth systems

KT Igulu, NR Saturday - 2024 - IET
Globally, healthcare services are being offered virtually with the combination of internet
technologies called a telehealth system. Telehealth system focuses on delivering healthcare …