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Al Khobar

As seen in: Nature, Elsevier, Frontiers, Global Finance Journal, Agriculture & Food Security, Biomed Central (BMC), International Business Times (U.S.), Journal of Medical Case Reports, The Minnesota Star Tribune, Royal Society of Chemistry and
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Articles

Residence Time Distribution in Tubular Flow Systems Using Machine Learning and Deep Learning Techniques. An Experimental and Predictive Modeling

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By Al Khobar, Gyanendra Kumar
| Frontiers
Abstract While the axial dispersion model can greatly simplify the intricacies of flow behavior in small-diameter tubes, its efficacy decreases with complex systems having heterogeneous properties. The proposed study assesses machine learning and deep learning for predictive analysis of complex nonlinear systems governing residence time distribution (RTD).
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Anisotropic Bianchi Type-V Generalized Ghost Pilgrim Dark Energy Cosmological Model in Self – Creation Gravity

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By Bhaskara Rao, Vasavi College, Al Khobar
| Frontiers
ORIGINAL RESEARCH article Volume 13 - 2026 | doi: 10.3389/fspas.2026.1873551 Reviewed by ORIGINAL RESEARCH article MB M.P.V.V. Bhaskara Rao 1 TR Tenneti Ramprasad 2 CV CH V V Ramana 3 FK Faten Karim 5 SM Samih Mostafa 6 1. Vignan's Institute of Information Technology, Visakhapatnam, India 2. Vasavi College of Engineering, Hyderabad, India 3. Vignan's Institute of Information Technology (VIIT), Visakhapatnam, India 4. Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia 5.
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Prevalence and Factors Associated With Post-Stroke Depression: A Cross-Sectional Analysis of a Prospectively Assembled Cohort in Eastern Saudi Arabia

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By Al Khobar, Al Qarni
| Frontiers
Abstract Abstract Objective: To estimate the prevalence and severity of post-stroke depression (PSD) and identify factors independently associated with PSD among stroke survivors. Methods: This cross-sectional analysis was conducted within a prospectively assembled hospital-based cohort at King Fahd University Hospital between January 2021 and November 2025.
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