Advanced machine learning techniques for cardiovascular disease early detection and diagnosis

NA Baghdadi, SM Farghaly Abdelaliem, A Malki… - Journal of Big Data, 2023‏ - Springer
The identification and prognosis of the potential for develo** Cardiovascular Diseases
(CVD) in healthy individuals is a vital aspect of disease management. Accessing the …

[HTML][HTML] A new approach in identifying the psychological impact of COVID-19 on university student's academic performance

ES Atlam, A Ewis, MM Abd El-Raouf, O Ghoneim… - Alexandria Engineering …, 2022‏ - Elsevier
COVID-19 was first discovered in Wuhan, China on December 2019. It is one of the worst
pandemics in human history. The education sector is one of the sectors most affected by the …

[PDF][PDF] Metaheuristic optimization algorithm for signals classification of electroencephalography channels

MM Eid, F Alassery, A Ibrahim… - Computers, Materials & …, 2022‏ - researchgate.net
Digital signal processing of electroencephalography (EEG) data is now widely utilized in
various applications, including motor imagery classification, seizure detection and …

Abmm: Arabic bert-mini model for hate-speech detection on social media

M Almaliki, AM Almars, I Gad, ES Atlam - Electronics, 2023‏ - mdpi.com
Hate speech towards a group or an individual based on their perceived identity, such as
ethnicity, religion, or nationality, is widely and rapidly spreading on social media platforms …

[PDF][PDF] Machine learning innovations in early cardiovascular disease detection

MK Saini - DOI: https://dx. doi. org/10.21275/SR23101210074, 2023‏ - researchgate.net
Identifying and predicting the risk of Cardiovascular Diseases (CVD) in healthy individuals is
crucial for effective disease management. Leveraging extensive health data available in …

Deep residual network with a cbam mechanism for the recognition of symmetric and asymmetric human activity using wearable sensors

S Mekruksavanich, A Jitpattanakul - Symmetry, 2024‏ - mdpi.com
Wearable devices are paramount in health monitoring applications since they provide
contextual information to identify and recognize human activities. Although sensor-based …

[HTML][HTML] Predicting personality traits with semantic structures and LSTM-based neural networks

MA Kosan, H Karacan, BA Urgen - Alexandria Engineering Journal, 2022‏ - Elsevier
There is a need to obtain more information about target audiences in many areas such as
law enforcement agencies, institutions, human resources, and advertising agencies. In this …

Summarization of text and image captioning in information retrieval using deep learning techniques

P Mahalakshmi, NS Fatima - IEEE Access, 2022‏ - ieeexplore.ieee.org
Automated information retrieval and text summarization concept is a difficult process in
natural language processing because of the infrequent structure and high complexity of the …

A comparative study: Toward an effective convolutional neural network architecture for sensor-based human activity recognition

Z Zhongkai, S Kobayashi, K Kondo, T Hasegawa… - IEEE …, 2022‏ - ieeexplore.ieee.org
The feature extraction of human activity recognition (HAR) based on sensor data has been
studied as a hand-crafted method. The significant feature extraction ability is a key factor in …

Comparing ARIMA and various deep learning models for long-term water quality index forecasting in Dez River, Iran

ARR Niknam, M Sabaghzadeh, A Barzkar… - … Science and Pollution …, 2024‏ - Springer
Water scarcity poses a significant global challenge, particularly in develo** nations like
Iran. Consequently, there is a pressing requirement for ongoing monitoring and prediction of …