Mr Adablanu, Selorm
Khalid, A.M., Boateng, O.O., Adablanu, S., and Yakubu, F. (2026). ICT Tools And Infrastructure: Foundations, Classifications and Applications in Agribusiness. In Foundations of ICT for Agribusiness: Digital Tools, Technologies and Transformations in Modern Agriculture. Deep Science Publishing, . DOI: https://doi.org/10.1201/9781003735113-15.
Sharma, T., Singh, A., Vahist, S., Jha, R.K., Mokdad, M., Domakani, M.R., Adablanu, S., Watfa, A.A. (2026). Effectiveness of Video-Assisted Teaching on Substance Abuse Knowledge among Adolescents. FMDB Transactions on Sustainable Techno Learning, 4(2), 80-90. DOI: https://doi.org/10.69888/FTSTL.2026.000747
Adablanu S. (2026). Deep Learning for Predicting Genome-Editing Outcomes. In Neelanjana C. , Jyoti P. S. , Dilip K. D. , Satyabrata N The Genome Editing Frontier. CRC Press-Taylor and Francis, . DOI: https://doi.org/10.1201/9781003735113-15.
Adablanu S. , Barman U., Das D. (2026). A Hybrid 1D-CNN and Transformer-Based Deep Learning Framework for Stroke Detection Using Brain CT Scans. Procedia Computer Science, 283, 446-455. DOI: https://doi.org/10.1016/j.procs.2026.06.129
Dake D.K., Ofori E., Adablanu S. (2026). From Education to Employment: A Deep Learning Approach to Understanding Job Market Trends in Africa. International Journal of Information and Education Technology, 16(4), 1007-1019. DOI: https://doi.org/10.18178/ijiet.2026.16.4.2571
Adablanu S. , Barman U., Das D. (2026). Comparative Efficacy of Focal and Binary Cross-Entropy Loss in Handling Class Imbalance for Stroke CT Classification. In 2026 Sixth International Conference on Advances in Electrical, Computing, Communications and Sustainable Technologies (ICAECT) IEEE, . DOI: https://doi.org/10.1109/ICAECT68478.2026.1...
Adablanu S. , Barman U., Das D. (2026). Transforming Skin Cancer Detection With AI‐Based Convolutional and Transformer Models. iRADIOLOGY, 4(1), 51-62. DOI: https://doi.org/10.1002/ird3.70058
Achulo C.S, Adablanu S. , Quaye D.A. (2026). Engaging 21st Century Learners and Differentiating Instruction with Multimedia: An Empirical Case Study of the University of Education, Winneba, Ghana. International Journal of Computer Applications, 975(83), 8887. DOI: https://doi.org/10.5120/ijca2026926453
Dweh T.J and Adablanu S. (2026). Feature Extraction and Selection Methods Outperform Machine Learning and Deep Learning Techniques. In Saurav Mallik, Zhongming Zhao, Soumita Seth, Aimin Li, Kasmika Borah, Himanish Shekhar Das Feature Selection and Feature Extraction on Omics Data. Chapman and Hall/CRC, . https://www.taylorfrancis.com/chapters/edit/10....
Adablanu S. , Barman U., Das D. (2025). 15 Years of Optimizers in Medical Deep Learning: A Systematic Review. Neuroscience Informatics, 6(1), 100249. DOI: https://doi.org/10.1016/j.neuri.2025.100249
Adablanu S. , Barman U., Das D. (2025). A novel hybrid adaptive transformer framework with multihead self attention for stroke detection. Discover Neuroscience, Volume 20(24), 025. DOI: https://doi.org/10.1186/s13064-025-00224-7
Adablanu S., Ghansah B., Benuwa BB. , Oppong SO. (2025). A Thorough Review of AI Developments in Education: Historical Progress, Current Applications, and Future Directions. Journal of Artificial Intelligence in Education, Volume 1(2), 52–63. DOI: https://doi.org/10.29303/jaie.v1i2.706
Matey PK. , Rubbin OA. ,Adablanu S. (2025). The Internet of Things in Education: Adoption Patterns and Learning Outcomes from a Ghanaian Case Study. International Journal of Computer Applications, 187(51), 32-41. DOI: https://doi.org/10.5120/ijca2025925811
Adablanu S. ,Barman U. ,Das D. (2025). Advancing deep learning for automated stroke detection: a review. Brain Hemorrhages, Volume 6(Issue 5), 247-260. DOI: https://doi.org/10.1016/j.hest.2025.07.002
Adablanu, S., Offei, M. & Boateng, A. (2024). Adopting sustainable mobile learning: Investigating long-term integration at UEW with a focus on infrastructure, resources, and institutional support. Advances in Mobile Learning Educational Research, 4(2), 1173-1189. DOI: https://doi.org/10.25082/AMLER.2024.02.011