Alamoodi, A.H.

A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion

Albahri, A. S., Duhaim, A. M., Fadhel, M. A., Alnoor, A., Baqer, N. S., Alzubaidi, L., Albahri, O. S., Alamoodi, A. H., Bai, J., Salhi, A., et al. (2023) · Information Fusion

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 716

Telehealth utilization during the Covid-19 pandemic: a systematic review

Garfan, S., Alamoodi, A. H., Zaidan, B. B., Al-Zobbi, M., Hamid, R. A., Alwan, J. K., Ahmaro, I. Y. Y., Khalid, E. T., Jumaah, F. M., Albahri, O. S., et al. (2021) · Computers in Biology and Medicine

Telemedicine and Telehealth ImplementationHealthcare during COVID-19 Pandemic

Cited by 369

How smart is e-tourism? A systematic review of smart tourism recommendation system applying data management

Hamid, R. A., Albahri, A. S., Alwan, J. K., Al-qaysi, Z. T., Albahri, O. S., Zaidan, A. A., Alnoor, A., Alamoodi, A. H., & Zaidan, B. B. (2021) · Computer Science Review

Recommender Systems and TechniquesDiverse Aspects of Tourism Research

Cited by 273

Fuzzy decision-making framework for explainable golden multi-machine learning models for real-time adversarial attack detection in Vehicular Ad-hoc Networks

Albahri, A. S., Hamid, R. A., Abdulnabi, A. R., Albahri, O. S., Alamoodi, A. H., Deveci, M., Pedrycz, W., Alzubaidi, L., Santamaría, J., & Gu, Y. (2024) · Information Fusion

Vehicular Ad Hoc Networks (VANETs)Adversarial Robustness in Machine Learning

Cited by 55

A Novel Evaluation Framework for Medical LLMs: Combining Fuzzy Logic and MCDM for Medical Relation and Clinical Concept Extraction

Alamoodi, A. H., Zughoul, O., David, D., Garfan, S., Pamucar, D., Albahri, O. S., Albahri, A. S., Yussof, S., & Sharaf, I. M. (2024) · Journal of Medical Systems

Multi-Criteria Decision MakingFuzzy and Soft Set Theory

Cited by 22