Journal of Artificial Intelligence and Digital Health

Ademola Olusola ADESINA is an academic staff member of Olabisi Onabanjo University, Ago-Iwoye, Nigeria. He obtained his First Degree, Master’s degree, and Ph.D. in Computer Science from Ogun State University (now Olabisi Onabanjo University), Ago-Iwoye, University of Ibadan, Nigeria, and the University of the Western Cape, Cape Town, South Africa, respectively.  His research interests fall within the areas of Information Systems, Software Engineering, E-health Systems, and ICT Applications. He has attended and presented papers in both local and international conferences within his area of research interest and has published many articles in reputable local and international journals. He lectures on Computer Science and Information Technology-related courses both at the Undergraduate and Postgraduate levels.

• Machine Learning and Data Analytics
• E-Health and Mobile Health Systems
• Information Systems and Software Engineering
• Cybersecurity and Cryptographic Systems
• ICT Applications for Development
• Internet of Medical Things (IoMT)
• Human–Computer Interaction

1. Supervision of undergraduate and postgraduate (PGD, MSc, PhD) research projects
2. Reviewer for international journals (IJCDS, IJISPDF, others)
3. Editorial Board Member – Journal of Computer Science and Its Applications (JCSA)
4. Member, Nigeria Computer Society (NCS) – multiple national committees
5. Conference paper presenter at international and national conferences
6. Head of Department, Computer Science (2024–2025)
7. Coordinator, Open and Distance Learning Programme

1. Short Message Service Normalization for Communication with a Health Information System
2. Text Messaging and Retrieval Techniques for a Mobile Health Information System
3. ICT and Information Security Perspectives in E-Health Systems
4. Using Wearable Sensors for Remote Healthcare Monitoring
5. Diagnosis of Cancer Ailment Using Expert System Model
6. A Multi-Agent Based Approach to SMS Normalization System
7. Performance Evaluation of Machine Learning Models for Clinical Diagnosis
8. Detection of Phishing URLs Using Supervised Machine Learning Algorithms
9. Bootstrapping Random Forest and CHAID for Disease Prediction
10. Predicting Cloud Computing Adoption in IoMT Using Deep Learning