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A researcher interested in integrating healthcare with emerging technologies.
Passionate to make a diverse educational environment in higher education.
Post-secondary education
Testing and grading
Curriculum Development
Student-centered learning
Curriculum Creation
Research And Analysis
Classroom Lecturing
Academic Research
Online learning tools
Technology-based curriculum
Student advocacy
Academic research
Academic advisement
Student counseling
Lecturing
Class instruction
C
C
Java
Android development
Python
PHP
Certificate in University Teaching and Learning
Healthcare Applications and Technologies
Wireless Network Security
Machine Learning
Deep Learning
Body Sensors Networks
Teaching in Higher Education
Education, Knowledge and Skills
Certificate in University Teaching and Learning
H. Allahem and S. Sampalli, "Automated Labour Detection Framework to Monitor Pregnant Women with a High Risk of Premature Labour Using Machine Learning and Deep Learning," Informatics in Medicine Unlocked, 2021.
H. Allahem and S. Sampalli, "Automated uterine contractions pattern detection framework to monitor pregnant women with a high risk of premature labour," Informatics in Medicine Unlocked, vol. 20, p. 100404, 2020. [Online]. Available: https://doi.org/10.1016/j.imu.2020.100404.
Aldughayfiq, B.; Allahem, H.; Mostafa, A.M.; Alnusayri, M.; Ezz, M. Layer-Weighted Attention and Ascending Feature Selection: An Approach for Seriousness Level Prediction Using the FDA Adverse Event Reporting System. Appl. Sci. 2024, 14, 3280. https://doi.org/10.3390/app14083280
H. Allahem and S. Sampalli, "Framework to monitor pregnant women with a high risk of premature labour using sensor networks," in Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management, 2017, pp. 1178-1181. [Online]. Available: https://ieeexplore.ieee. org/document/7987458.
"Survey of techniques for automatic detection of premature labour," The European Society of Medicine’s Annual Congress (ESMED), 2021.