1. Folorunso, S. O. and Adeyemo, A. B. (2013): Alleviating Classification Problem of Imbalanced Dataset. African Journal of Computing and ICTs. (A Journal of the Institute of Electrical and Electronics Engineers (IEEE), Computer Chapter. 6 (2): 137 – 144. ISSN 2006- 1781. NIGERIA.

2. Folorunso, S. O. and Adeyemo, A. B.  (2016) Improved data sampling schemes for alleviating class imbalance problem. Journal of Science Research (JSR), University of Ibadan, Ibadan, Nigeria. 15: 10-15. ISSN 1119 7333.                         NIGERIA.

3. Folorunso, S. O. and Adeyemo, A. B. (2017): An Empirical Experimental Survey of Application of Wilson’s Edited Nearest Neighbour as a Sampling and Data Reduction Scheme to Alleviate Class Imbalance Problem. Journal of the Nigerian Association of Mathematical Physics (NAMP). 42:239-248  Folorunso, S. O. and Adeyemo, A. B. (2018): Empirical Study of Enhanced Sampling Schemes with Ensembles to Alleviate the Class Imbalance Problem. Ife Journal of Science and Technology (IFEJOST), Obafemi Awolowo University, Ile-Ife, Nigeria.  2(1):22-35    NIGERIA.

4. Abdullah, K-K. A, Folorunso, S. O., Solanke, O. O, and Sodimu, S. M. (2018). A Predictive Model for Tweet Sentiment Analysis and Classification.  Anale. Seria Informatică (Annals. Computer Science Series) of Universitatea “Tibiscus” din Timişora (“Tibiscus” University of Timişora). 16(2):35-44. http://anale-informatica.tibiscus.ro/?page=04_indexautori&link=folorunso-so         ROMANIA

5. Ayo F. E., Folorunso O., Folorunso S. O. (2018): CA-KSE: A Combinatorial Algorithm for Benchmarking in Knowledge Sharing Environment. International Journal of Intelligent Computing and Cybernetics. 12(1): 2-22 https://doi.org/10.1108/IJICC-12-2017-0158                                            United Kingdom.

6. Folorunso, S. O., Taiwo, A. I., Olabanjo, O. E (2018): A Predictive Model for Estimating Petroleum Consumption Using Machine Learning Approach. LAUTECH Journal of Engineering and Technology, (LAUJET). 12(2): 80-87                                 NIGERIA

7. Folorunso, S. O., Ayo, F. E., Adigun, A. A., Olaniyan, O. E. (2019): Evaluation of Multi-Target Regression Models on Africa Soil Properties. University of Pitesti Scientific Bulletin: Electronics and Computers Science of Universitatii din Pitesti.  19(1): 1-8                        ROMANIA

8. Folorunso S. O., Taiwo, A. I., Olatayo, T. O. (2019): Empirical Comparison of Time Series Data Mining Algorithms. Indonesian Journal of Computing (Indo-JC). School of Computing, Telkom University. 4(2): 109-118.  doi:10.21108/indojc.2019.4.2.329      INDONESIA

9. Adeboye, N. O., Abimbola, O. V., Folorunso, S. O. (2020). Malaria Patients in Nigeria: Data Exploration Approach. Data in Brief. 28:104997 doi.org/10.1016/j.dib.2019.104997. Elsevier, Netherlands.                                                      

10. Ayo, F. E., Awotunde, J. B., Ogundokun, R. O., Folorunso S. O., Adekunle, A. O.,  (2020): A decision support system for multi-target disease diagnosis: A Bioinformatics Approach. Heliyon.  6: e03657. https://doi.org/10.1016/j.heliyon.2020.e03657 Elsevier, Netherlands.

11. Folorunso, S. O., Fashooto, S. G., Olaomi, J., Fashooto, O. Y. (2020): A Multi-Label Learning Model for Psychotic Diseases in Nigeria. Informatics in Medicine Unlocked. 19: 100326. https://doi.org/10.1016/j.imu.2020.100326 Elsevier, United Kingdom. 

12. Taiwo, A. I., Folorunso, S. O., Gbadamosi, Solafunmi C. (2020): Statistical Analysis of Examination Malpractice Concepts in Nigeria. Bulgarian Journal of Science and Education Policy (BJSEP), University of Sofia (Bulgaria). 14(1): 41-53. Bulgaria, Europe

13. Ayo, F. E, Folorunso, S. O., Abayomi-Alli, A. A., Adekunle, A. O., Awotunde, J. B. (2020): Network intrusion detection based on deep learning model optimized with rule-based hybrid feature selection. Information Security Journal: A Global Perspective. 29(6): 267-283. https://doi.org/10.1080/19393555.2020.1767240 Taylor & Francis, United Kingdom

14. Ogundepo, E. A., Folorunso, S. O., Adekanmbi, O., Akinsande, O., Banjo, O. O., Ogbuju, E., Oladipo, F. O., Abimbola, O., Oseghale, E., Babajide, O. (2020) An Exploratory Assessment of a Multidimensional Healthcare and Economic Data on COVID-19 in Nigeria. Data in Brief. 33:106424. https://doi.org/10.1016/j.dib.2020.106424 Elsevier, Netherlands. 

15. Folorunso, S. O., Ayo, F. E., Abdullah, K-K. A., Ogunyinka, P. I (2020): Hybrid Vs Ensemble of Classification Model for Phishing Website Classification.  Iraqi Journal of Science. 61(12):3387-3396. https://doi.org/ 10.24996/ijs.2020.61.12.27 IRAQ

16. Onafeso, O. D., Onafeso, T. O., Olumuyiwa-Oluwabiyi, G. T., Faniyi, M. O., Olusola, A. O., Dina, A. O., Hassan, A. M., Folorunso, S. O., Adelabu, S., Adagbasa, E. (2021): Geographical Trend Analysis of COVID-19 Pandemic Onset in Africa. Social Sciences & Humanities Open. 4(1): 100137. https://doi.org/10.1016/j.ssaho.2021.100137 Elsevier. The Netherlands.

17. Elujide, I., Fashoto, S. G., Fashoto, B., Mbunge, E., Folorunso, S. O., Olamijuwon, J. O. (2021). Application of Deep and Machine Learning Techniques for Multi-Label Classification Performance on Psychotic Disorder Diseases. Informatics in Medicine Unlocked. 23:100545. https://doi.org/10.1016/j.imu.2021.100545. Elsevier

18. Mirjam van Reisen, M., Oladipo, F., Stokmans, M., Mpezamihgo, M., Folorunso, S, Schultes, E., Basajja, M., Aktau, A., Yohannes, S., Amare, Taye, G. T., Yati, P. H. P., Chindoza, K., Wirtz, M., Ghardallou, M., van Stam, G., Ayele, W., Nalagala, N., Abdullahi, I., Osigwe, O., Graybeal, J., Medhanie, A. A., Kawu, A. A., Liu, L., Wolstencroft, K., Flikkenschild, E., Lin, Y., Stocker, J., Musen, M. (2021). Design of a FAIR Digital Data Health Infrastructure in Africa for COVID-19 Reporting and Research. Advanced Genetics. Wiley DOI: https://doi.org/10.1002/ggn2.10050

19. Afolabi, S., Warrie, W., Banjo, O. O., Iwashokun, O., Abimbola, O., Ngqambela, N., Soliu, F., Olasunkanmi, O., Folorunso, S. O., Matshika, S. (2021). When & where?  Proactively Predicting Traffic Accident in South Africa: Our Machine Learning Competition Winning Approach. International Journal of Society System Science (IJSSS). 13(2):151-170. https://doi.org/10.1504/IJSSS.2021.116374 Inderscience, United Kingdom 

20. Folorunso, S. O., Afolabi, S. A., Owodeyi, A. B. (2021): Dissecting Genre of Nigerian Music with Machine Learning. Journal of King Saud University - Computer and Information Science https://doi.org/10.1016/j.jksuci.2021.07.009 Saudi Arabia 

21. Folorunso S.O., Ogbuju E., Oladipo F. (2021) Artificial Intelligence and the Control of COVID-19: A Review of Machine and Deep Learning Approaches. In: Oliva D., Hassan S.A., Mohamed A. (eds) Artificial Intelligence for COVID-19. Studies in Systems, Decision and Control, vol 358. Chapter 10 pp 167-185. Springer, Cham. https://doi.org/10.1007/978-3-030-69744-0_10  SPRINGER Nature Switzerland AG

22. Ghardallou, M., Wirtz, M., Folorunso, S., Touati, Z., Ogundepo, E., Smits, K., Mtiraoui, A., van Reisen, M. (2022) Expanding Non-Patient COVID-19 Data: Towards the FAIRification of Migrants' Data in Tunisia, Libya and Niger. Data Intelligence. 4(4): 955–970. doi: https://doi.org/10.1162/dint_a_00181 Chinese Academy of Sciences.

23. Folorunso, S., Ogundepo, E., Basajja, M., Awotunde, J., Kawu, A., Oladipo, F., Ibrahim, A. (2022)   FAIR Machine Learning Model Pipeline Implementation of COVID-19 Data. Data Intelligence. 4(4): 971–990. doi: https://doi.org/10.1162/dint_a_00182 Chinese Academy of Sciences.

24. Awotunde, J.B., Folorunso, S.O., Imoize, A.L., Odunuga, J.O., Lee, C.-C., Li, C.-T., Do, D.-T. (2023) An Ensemble Tree-Based Model for Intrusion Detection in Industrial Internet of Things Networks. Applied Sciences. 13:2479. https://doi.org/10.3390/app13042479 MDPI, Switzerland

25. Adeboye, N. O., Folorunso, S. O., Abimbola, O. V., & Akinbo, R. Y. (2023). Modelling the volatility of African capital markets in the presence of the Covid-19 pandemic: evidence from five emerging economies in Africa. Statistics in Transition new series, 24(2), 17-37. http://doi.org/10.59170/stattrans-2023-018  

26. Folorunso, S. O., Awotunde, J. B., Rangaiah, Y. P., Ogundokun, R. O. (2023). EfficientNets Transfer Learning Strategies for Hispathological Breast Cancer Image Analysis. International Journal of Modeling, Simulation, and Scientific Computing. https://doi.org/10.1142/S1793962324410095 World Scientific Publishing Company.

27. Ayo, F. E., Awotunde, J. B., Folorunso, S. O., Adigun, M. O., Ajagbe, S. A. (2023). A genomic rule-based KNN model for fast flux botnet detection. Egyptian Informatics Journal. 24(2):313-325. https://doi.org/10.1016/j.eij.2023.05.002. Elsevier BV on behalf of Faculty of Computers and Artificial Intelligence, Cairo University.

28. Folorunso, S. O., Awotunde, J. B., Adigun, A. A., Prasad, L. V. N., Lalitha, V. L. (2023) A hybrid model for post-treatment mortality rate classification of patients with breast cancer. Healthcare Analytics. 4: 100254. https://doi.org/10.1016/j.health.2023.100254.  Elsevier

29. Folorunso, S. O., Awotunde, J. B., Adigun, A. A., Panigrahi, R., Garg, A., Bhoi, A. K. (2023). Multi‑Label Learning Model for Diabetes Disease Comorbidity. J. Inst. Eng. India Ser. B. https://doi.org/10.1007/s40031-023-00913-z  Springer

30. Awotunde, J. B., Gaber, T., Prasad, L. N., Folorunso, S. O., & Lalitha, V. L. (2023). Privacy and Security Enhancement of Smart Cities using Hybrid Deep Learning-enabled Blockchain. Scalable Computing: Practice and Experience, 24(3), 561-584. https://doi.org/10.12694/scpe.v24i3.2272 Institute e-Austria Timisoara, Romania.

31. Awotunde J.B., Folorunso S.O., Jimoh R.G., Adeniyi E.A., Abiodun K.M., Ajamu G.J. (2021) Application of Artificial Intelligence for COVID-19 Epidemic: An Exploratory Study, Opportunities, Challenges, and Future Prospects. In: Oliva D., Hassan S.A., Mohamed A. (eds) Artificial Intelligence for COVID-19. Studies in Systems, Decision and Control (SSDC), vol 358. Chapter 4 pp. 47-61. ISBN 978-3-030-69743-3. Springer, Cham. https://doi.org/10.1007/978-3-030-69744-0_4 SPRINGER Nature Switzerland AG

32. Folorunso S.O., Awotunde J.B., Ayo F.E., Abdullah KK.A. (2021) RADIoT: The Unifying Framework for IoT, Radiomics and Deep Learning Modeling. In: Kumar Bhoi A., Mallick P.K., Narayana Mohanty M., Albuquerque V.H.C. (eds) Hybrid Artificial Intelligence and IoT in Healthcare. Intelligent Systems Reference Library, vol 209. Chapter 6 pp. 109-128. Springer, Singapore. https://doi.org/10.1007/978-981-16-2972-3_6

33. Awotunde J., Folorunso S.O., Bhoi A.K., Adebayo P.O., Ijaz M.F. (2021) Disease Diagnosis System for IoT-Based Wearable Body Sensors with Machine Learning Algorithm. In: Kumar Bhoi A., Mallick P.K., Narayana Mohanty M., Albuquerque V.H.C. (eds) Hybrid Artificial Intelligence and IoT in Healthcare. Intelligent Systems Reference Library, vol 209. Chapter 10 pp. 201-222. Springer, Singapore. https://doi.org/10.1007/978-981-16-2972-3_10

34. Folorunso S.O., Awotunde J.B., Adeboye N.O., Matiluko O.E. (2022) Data Classification Model for COVID-19 Pandemic. In: Hassanien AE., Elghamrawy S.M., Zelinka I. (eds) Advances in Data Science and Intelligent Data Communication Technologies for COVID-19. Studies in Systems, Decision, and Control, vol 378. Chapter 6 pp. 93-118. Springer, Cham. https://doi.org/10.1007/978-3-030-77302-1_6 Springer Nature Switzerland AG

35. Awotunde J.B., Jimoh R.G., AbdulRaheem M., Oladipo I.D., Folorunso S.O., Ajamu G.J. (2022) IoT-Based Wearable Body Sensor Network for COVID-19 Pandemic. In: Hassanien AE., Elghamrawy S.M., Zelinka I. (eds) Advances in Data Science and Intelligent Data Communication Technologies for COVID-19. Studies in Systems, Decision, and Control, vol 378. Chapter 6 pp. 253-275. Springer, Cham. https://doi.org/10.1007/978-3-030-77302-1_14 Springer Nature Switzerland AG

36. Awotunde, J. B., Folorunso, S. O., Chakraborty, C., Bhoi, A. K., & Ajamu, G. J. (2022). Application of artificial intelligence and big data for fighting COVID-19 pandemic. Decision Sciences for COVID-19: Learning Through Case Studies, 3-26. Cham: Springer International Publishing.

37. Awotunde, J. B., Folorunso, S. O., Ajagbe, S. A., Garg, J., & Ajamu, G. J. (2022). AiIoMT: IoMT-based system-enabled artificial intelligence for enhanced smart healthcare systems. Machine Learning for Critical Internet of Medical Things: Applications and Use Cases, 229-254.

38. Folorunso, S. O., Ogundepo, E. A., Awotunde, J. B., Ayo, F. E., Banjo, O. O., & Taiwo, A. I. (2022). A Multi-Step Predictive Model for COVID-19 Cases in Nigeria Using Machine Learning. In Decision Sciences for COVID-19: Learning Through Case Studies, 107-136. Cham: Springer International Publishing.

Published Conference Proceedings:  

1. Folorunso, S. O. and Adeyemo, A. B. (2012): Class Imbalance: A Review. The 7th International Proceedings on ICT Applications (AICTTRA 2012). E. R. Adagunodo, G.A. Aderounmu and A. O. Oluwatope (Eds). Pp. 19-24. ISSN 2141-0240 (National Defence College, Abuja, Nigeria)

2. Folorunso, S. O. and Adeyemo, A. B. (2012): Theoretical Comparison of Undersampling Techniques Against Their Underlying Data Reduction Techniques, EIE’s 2nd International Conference on Computing, Energy, Networking, Robotics and Telecommunications (EIECON 2012). S. N. John, C. U. Ndujiba, F. A. Ibikunle and J. O. Onaolapo (Eds.). Pp. 92-97. ISBN 978-37963-8-0 (Covenant University, Nigeria).  

3. Folorunso, S. O. and Adeyemo, A. B. (2013): Alleviating Class Imbalance Problem. In the Proceedings of Interrnational Multidisciplinary Conference on Research, Developments and Practices in Science, Technology, Education, Arts, Management and theSocial Sciences (iSTEAMS) Research Nexus 2013. S. C. Chiemeke, Richard Boateng, Olumide longe, Folajimi Yetunde and Colin Tharkur (Eds.), Series 4, Vol. 3, pp. 223 - 232. (Research Nexus Africa, CREATE and African Institute of Development Informatics and policy, Ghana). 

4. Fitkov-Norris E. and Folorunso S.O. (2013) Impact of Sampling on Neural Network Classification Performance in the Context of Repeat Movie Viewing. In: Iliadis L., Papadopoulos H., Jayne C. (eds) Engineering Applications of Neural Networks.   EANN 2013. Communications in Computer and Information Science, vol 383. Springer, Berlin, Heidelberg  

5. Ayo, F. E, Awotunde, J. B., Folorunso, S. O. Ogundokun, R. O., Idoko, P. S., Adekunle, J. I. and Oladipo, I. D. (2018). A Fuzzy Based Method for Diagnosis of Acne Skin Disease Severity. In the Proceedings of the 2nd International Conference on Information and Communication Technology and Its Applications (ICTA2018). Pp 343-349 

6. Folorunso S.O., Awotunde J.B., Adeniyi E.A., Abiodun K.M., Ayo F.E. (2022) Heart Disease Classification Using Machine Learning Models. In: Misra S., Oluranti J., Damaševičius R., Maskeliunas R. (eds) Informatics and Intelligent Applications. ICIIA 2021. Communications in Computer and Information Science, vol 1547, pp 35-49. Springer, Cham. https://doi.org/10.1007/978-3-030-95630-1_3  

7. Awotunde J.B., Abiodun K.M., Adeniyi E.A., Folorunso S.O., Jimoh R.G. (2022) A Deep Learning-Based Intrusion Detection Technique for a Secured IoMT System. In: Misra S., Oluranti J., Damaševičius R., Maskeliunas R. (eds) Informatics and Intelligent Applications. ICIIA 2021. Communications in Computer and Information Science, vol 1547, pp 50-62. Springer, Cham. https://doi.org/10.1007/978-3-030-95630-1_4