Biomedical Intelligence Systems Lab
Where biomedical data meets intelligent, secure software.
BISL is a cloud-native, interdisciplinary research group at Babcock University. Biomedical informatics is its anchor, machine learning its engine, and secure, well-built software its systems layer.
Research
Five themes, one lab.
01
Biomedical informatics and data-driven discovery
Clinical and genomic data turned into evidence for diagnosis and treatment.
02
Artificial intelligence and intelligent systems
Machine learning and deep learning models built for decisions people actually make.
03
Secure and trustworthy computing
Systems that protect sensitive health and institutional data.
04
Software systems and platform innovation
Research that ships as working software and digital platforms.
05
Emerging interdisciplinary innovation
Questions between disciplines that need more than one method.
Aligned to UN Sustainable Development Goals: 3, 4, 9, 16
The lab
People
Ernest E. Onuiri
Lab lead
Biomedical informatics, clinical decision support, ML in cancer diagnostics, explainable AI
Publications
Selected work
2026 · Chapter
Hybrid deep learning model for reversible image steganography
Nzenwata UJ, Haruna OI, Osilaja D, Ayankoya F, Onuiri E, Awodele S, et al.
Intelligent Systems Reference Library, Springer
A hybrid deep learning model that hides data inside images and restores the original image exactly.
2026 · Journal
Spatio-temporal dynamics, clustering, and hotspot evolution of reported foot-and-mouth disease outbreak burden in Nigeria, 2015–2025
Awoseyi AA, Onuiri EE, Olarinmoye AO, Ademola MM, Adebowale OO
Scientific Reports
Maps a decade of reported foot-and-mouth disease outbreaks across Nigeria to show where and when the burden clusters.
2025 · Journal
Perspective on ethical AI in computational epidemiology and One Health with COHRCIE framework and computational prophylaxis
Awoseyi AA, Onuiri EE, Olarinmoye AO, Oguntola AU, Adebowale OO
Discover Public Health 22, 459
Proposes the COHRCIE framework for using AI ethically in computational epidemiology and One Health.
2024 · Journal
Enhancing car plate recognition with convolutional neural network and regular expressions correction
Awoseyi AA, Timothy TF, Ajagbe SA, Onuiri EE, Abdulahi QO, et al.
IAES International Journal of Artificial Intelligence 13(2), 2073-2080
Pairs a convolutional neural network with rule-based correction to read number plates more accurately.
2023 · Dataset
A dataset for predicting Supreme Court judgments in Nigeria
Ngige OC, Ayankoya FY, Balogun JA, Onuiri E, Agbonkhese C
Data in Brief 50, 109483
An openly published dataset that lets others train and test models on Nigerian Supreme Court judgments.
2023 · Journal
A systematic review of machine learning prediction models for colorectal cancer patient survival using clinical data and gene expression profiles
Onuiri EE, Akande O, Kalesanwo OB, Adigun T, Rosanwo K, Umeaka KC
Revue d'Intelligence Artificielle 37(5), 1273-1280
Reviews how machine learning models combine clinical and gene expression data to predict colorectal cancer survival.
2023 · Journal
Design and analysis of an automated IoT system for data flow optimization in higher education institutions
Adegbenjo AA, Onuiri EE, Kalesanwo OB, Agbaje MO, Abel SB, et al.
Journal Européen des Systèmes Automatisés 56(5), 889-897
An automated Internet of Things design for moving data efficiently across a university.
2020 · Thesis
Clinical associations and genetic alterations to predict radiotherapy treatment response in patients with triple negative breast cancer (TNBC)
Onuiri EE
PhD dissertation, Rutgers, The State University of New Jersey
Reads clinical features and genetic alterations together to anticipate radiotherapy response in triple-negative breast cancer.
Join
Do research that ships.
We supervise undergraduate, masters and doctoral researchers across biomedical informatics, machine learning and secure systems. If you want to turn health data into working, trustworthy software, we would like to hear from you.