Emonena Patrick Obrik-Uloho, Oluwaseun Oladeji Olaniyi, Olubukola Omolara Adebiyi, Rukayat Oluwabukola Olasege & Seun Michael Oyekunle·Asian Journal of Research in Computer Science·2025
This study developed a predictive framework to uncover underreported clinical signals hidden within dark data in digital health systems, addressing the paradox of abundant data but limited insights. It highlighted the importance of dark data, unanalyzed clinical records and the p...
Open access
Research Article10.9734/ajrcos/2025/v18i11779
Emonena Patrick Obrik-Uloho, Gbenro Charles Opeke, Adebayo Yusuf Balogun, Rukayat Oluwabukola Olasege & Lisa Mmesoma Udechukwu·Journal of Engineering Research and Reports·2025
This research developed a predictive and cybersecurity-aware framework to uncover and leverage underreported clinical and operational signals within dark data embedded in digital health ecosystems. Addressing the paradox of data-rich yet insight-poor healthcare systems, the study...
Open access
Research Article10.9734/jerr/2025/v27i111696
This study develops and validates an information governance framework for AI-generated synthetic patient data in healthcare research, balancing data utility, privacy, and algorithmic bias mitigation. The introduction positions the framework as a response to stringent privacy regu...
Open access
Research Article10.9734/ajarr/2025/v19i111193
Chukwudalu Henry Egonwanne, Oluwaseun Oladeji Olaniyi, Adebukola Oluyinka Eweoya, Emonena Patrick Obrik-Uloho & Rukayat Oluwabukola Olasege·Asian Journal of Research in Computer Science·2025
Ensuring privacy in AI-driven telehealth analytics remains a persistent challenge, as conventional cryptographic methods struggle to meet real-time and compliance requirements. This research developed and validated an AI-driven homomorphic encryption framework for secure real-tim...
Open access
Research Article10.9734/ajrcos/2025/v18i11775
Lisa Mmesoma Udechukwu, Oluwadayo Mafolasere Olaniyi, Adebukola Oluyinka Eweoya, Omobolaji Olufunmilayo Olateju & Rukayat Oluwabukola Olasege·Asian Journal of Research in Computer Science·2025
This research developed a blockchain-enabled framework to enhance secure credentialing and access management for remote healthcare providers and patients across fragmented digital health platforms. Addressing inefficiencies in traditional systems such as lengthy verification dela...
Open access
Research Article10.9734/ajrcos/2025/v18i11776
Seun Michael Oyekunle, Oluwaseun Oladeji Olaniyi, Emonena Patrick Obrik-Uloho, Olufisayo Juliana Tiwo & Rukayat Oluwabukola Olasege·Journal of Engineering Research and Reports·2025
This study investigates self-healing health records through the development of autonomous data integrity models for corruption-resistant Electronic Medical Records (EMRs). Using a convergent parallel mixed-methods design, a systematic review of 204 studies (2010–2025) identified...
Open access
Research Article10.9734/jerr/2025/v27i111685
Lisa Mmesoma Udechukwu, Tunbosun Oyewale Oladoyinbo, Nanyeneke Ravana Mayeke, Temilade Oluwatoyin Adesokan-Imran & Rukayat Oluwabukola Olasege·Archives of Current Research International·2025
This study developed and assessed an AI-driven adversarial defense framework using Generative Adversarial Networks (GANs) to secure healthcare IoT ecosystems against rising cybersecurity threats in medical settings. The research drew on datasets (CICIoMT2024, WUSTL-EHMS-2020, BoT...
Open access
Research Article10.9734/acri/2025/v25i101556
Emonena Patrick Obrik-Uloho, Valerie Ojinika Ejiofor, Chukwudalu Henry Egonwanne, Faith Hauwa Oluwapamilerin Kolo & Rukayat Oluwabukola Olasege·Archives of Current Research International·2025
The rapid digital transformation of healthcare through smart hospitals driven by AI, IoMT, cloud computing, and telemedicine has heightened cyber vulnerabilities, with 276 million records breached globally in 2024. This study developed a Zero Trust Architecture (ZTA) blueprint to...
Open access
Research Article10.9734/acri/2025/v25i101557
Seun Michael Oyekunle, Oluwadayo Mafolasere Olaniyi, Adebukola Oluyinka Eweoya, Michael Olayinka Gbadebo & Rukayat Oluwabukola Olasege·Journal of Engineering Research and Reports·2025
The growing complexity and volume of health data have exposed critical limitations in traditional, static data processing systems, creating an urgent need for adaptive AI pipelines that can support scalable, secure, and governance-compliant population health analytics. This study...
Open access
Research Article10.9734/jerr/2025/v27i101677