Application of artificial intelligence in wearable devices: Opportunities and challenges

D Nahavandi, R Alizadehsani, A Khosravi… - Computer Methods and …, 2022 - Elsevier
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …

[HTML][HTML] Epileptic seizures detection using deep learning techniques: a review

A Shoeibi, M Khodatars, N Ghassemi, M Jafari… - International journal of …, 2021 - mdpi.com
A variety of screening approaches have been proposed to diagnose epileptic seizures,
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …

The internet of medical things and artificial intelligence: trends, challenges, and opportunities

K Kakhi, R Alizadehsani, HMD Kabir, A Khosravi… - Biocybernetics and …, 2022 - Elsevier
High quality and efficient medical service is one of the major factors defining living
standards. Developed countries strive to make their healthcare systems as efficient and cost …

[HTML][HTML] A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models

Y Alali, F Harrou, Y Sun - Scientific Reports, 2022 - nature.com
This study aims to develop an assumption-free data-driven model to accurately forecast
COVID-19 spread. Towards this end, we firstly employed Bayesian optimization to tune the …

Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization

SX Lv, L Wang - Applied Energy, 2022 - Elsevier
This study proposes an effective combined model system for wind speed forecasting tasks.
In this model,(a) improved hybrid time series decomposition strategy (HTD) is developed to …

[HTML][HTML] Machine learning (ML) in medicine: Review, applications, and challenges

AM Rahmani, E Yousefpoor, MS Yousefpoor… - Mathematics, 2021 - mdpi.com
Today, artificial intelligence (AI) and machine learning (ML) have dramatically advanced in
various industries, especially medicine. AI describes computational programs that mimic and …

[HTML][HTML] Forecasting cryptocurrency prices using LSTM, GRU, and bi-directional LSTM: a deep learning approach

PL Seabe, CRB Moutsinga, E Pindza - Fractal and Fractional, 2023 - mdpi.com
Highly accurate cryptocurrency price predictions are of paramount interest to investors and
researchers. However, owing to the nonlinearity of the cryptocurrency market, it is difficult to …

[HTML][HTML] Multivariate time-series blood donation/demand forecasting for resilient supply chain management during COVID-19 pandemic

M Shokouhifar, M Ranjbarimesan - Cleaner Logistics and Supply Chain, 2022 - Elsevier
COVID-19 has caused negative impacts on blood supply chain management, due to
uncertain supply/demand and logistical disruptions. In the early weeks following the COVID …

[HTML][HTML] Improved LSTM-based deep learning model for COVID-19 prediction using optimized approach

L Zhou, C Zhao, N Liu, X Yao, Z Cheng - Engineering applications of …, 2023 - Elsevier
Individuals in any country are badly impacted both economically and physically whenever
an epidemic of infectious illnesses breaks out. A novel coronavirus strain was responsible …

The negative impact of the COVID-19 on renewable energy growth in developing countries: Underestimated

S Li, Q Wang, X Jiang, R Li - Journal of Cleaner Production, 2022 - Elsevier
Abstract According to the United Nations Environment Programme, the COVID-19 pandemic
has created challenges for the economy and the energy sector, as well as uncertainty for the …