SelectedWorks - Tayo Obafemi-Ajayi

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Selected Works of Tayo Obafemi-Ajayi

Adjunct Professor

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About Tayo Obafemi-Ajayi

Present	Adjunct Professor, Missouri University of Science and Technology
Institution Organization Position Type Position Title Time Period to Options Current Position Affiliate my profile with this Institution

Electrical and Computer Engineering

Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory

Information (Switzerland) (2024)

Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, et al.

Biomedical Datasets Distill Many Mechanisms Of Human Diseases, Linking Diseases To Genes And Phenotypes (Signs And Symptoms Of Disease), Genetic ...

Multiple Imputation For Robust Cluster Analysis To Address Missingness In ...

IEEE Access (2024)

Arnold Harder, Gayla R. Olbricht, Godwin Ekuma, Daniel B. Hier, et al.

Cluster Analysis Has Been Applied To A Wide Range Of Problems As An Exploratory Tool To Enhance Knowledge Discovery. Clustering ...

An Explainable Deep Learning Model For Prediction Of Severity Of ...

CIBCB 2023 - 20th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (2023)

Godwin Ekuma, Daniel B. Hier and Tayo Obafemi-Ajayi

Deep Convolutional Neural Networks (CNNs) have become the go-To method for medical imaging classification on various imaging modalities for binary ...

Connecting Phenotype To Genotype: PheWAS-inspired Analysis Of Autism Spectrum Disorder

Frontiers in Human Neuroscience (2022)

John Matta, Daniel Dobrino, Dacosta Yeboah, Swade Howard, et al.

Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of ...

NBT (No-Boundary Thinking): Needed To Attend To Ethical Implications Of ...

Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2022 (2022)

Joan Peckham, Andy Perkins, Tayo Obafemi-Ajayi and Xiuzhen Huang

In this era of Big Data and AI, expertise in multiple aspects of data, computing, and the domains of application ...

Team Building Without Boundaries

Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2022 (2022)

Andy Perkins, Joan Peckham, Tayo Obafemi-Ajayi and Xiuzhen Huang

Team building can be challenging when participants are from the same discipline or sub-discipline, but needs special attention when participants ...

Blood Biomarkers for Mild Traumatic Brain Injury: A Selective Review ...

Biomarker Research (2021)

Daniel B. Hier, Tayo Obafemi-Ajayi, Matthew S. Thimgan, Gayla R. Olbricht, et al.

Background: The use of blood biomarkers after mild traumatic brain injury (mTBI) has been widely studied. We have identified eight ...

A Kinetic Model for Blood Biomarker Levels after Mild Traumatic ...

Frontiers in Neurology (2021)

Sima Azizi, Daniel B. Hier, Blaine Allen, Tayo Obafemi-Ajayi, et al.

Traumatic brain injury (TBI) imposes a significant economic and social burden. The diagnosis and prognosis of mild TBI, also called ...

Heterogeneity in Blood Biomarker Trajectories after Mild TBI Revealed by ...

IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021)

Lien A. Bui, Dacosta Yeboah, Louis Steinmeister, Sima Azizi, et al.

Concussions, also known as mild traumatic brain injury (mTBI), are a growing health challenge. Approximately four million concussions are diagnosed ...

Noise Optimizes Super-Turing Computation In Recurrent Neural Networks

Physical Review Research (2021)

Emmett Redd, Steven Senger and Tayo Obafemi-Ajayi

This paper explores the benefit of added noise in increasing the computational complexity of digital recurrent neural networks (RNNs). The ...

Predictive Modeling of Sports-Related Concussions using Clinical Assessment Metrics

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence (2020, Canberra, Australia) (2021)

Sujit Subhash, Tayo Obafemi-Ajayi, Dennis Goodman, Donald C. Wunsch, et al.

Concussions represent a growing health concern that are challenging to diagnose and manage. Roughly four million concussions are diagnosed every ...

A Deep Learning Model to Predict Traumatic Brain Injury Severity ...

2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021 (2021)

Dacosta Yeboah, Hung Nguyen, Daniel B. Hier, Gayla R. Olbricht, et al.

For Many Neurological Disorders, Including Traumatic Brain Injury (TBI), Neuroimaging Information Plays a Crucial Role Determining Diagnosis and Prognosis. TBI ...

A PheWAS Model Of Autism Spectrum Disorder

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2021)

John Matta, Daniel Dobrino, Swade Howard, Dacosta Yeboah, et al.

Children with Autism Spectrum Disorder (ASD) exhibit a wide diversity in type, number, and severity of social deficits as well ...

Noise Quality And Super-Turing Computation In Recurrent Neural Networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2021)

Emmett Redd and Tayo Obafemi-Ajayi

Noise and stochasticity can be beneficial to the performance of neural networks. Recent studies show that optimized-magnitude, noise-enhanced digital recurrent ...

Statistical Comparative Analysis and Evaluation of Validation Indices for Clustering ...

2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (2020)

Thy Nguyen, Jason Viehman, Dacosta Yeboah, Gayla R. Olbricht, et al.

Clustering is a relevant exploratory tool for a broad range of machine learning applications as it aids identification of meaningful ...

An Explainable and Statistically Validated Ensemble Clustering Model Applied to ...

IEEE Access (2020)

Dacosta Yeboah, Louis Steinmeister, Daniel B. Hier, Bassam Hadi, et al.

We present a framework for an explainable and statistically validated ensemble clustering model applied to Traumatic Brain Injury (TBI). The ...

Exploratory Analysis of Concussion Recovery Trajectories using Multi-Modal Assessments and ...

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2020) (2020)

Zachary Roy, Sujit Subhash, Lien A. Bui, Bassam Hadi, et al.

Clinicians need better tools to assess severity, prognosis, and recovery from mild Traumatic Brain Injury (mTBI), which can cause long ...

Improved Classification Of Medical Data Using Meta-Best Feature Selection

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2020)

Matthew Chaplin, Jacob Grubb, Thomas Clifford, Justin Bruce, et al.

Feature selection provides a useful method for reducing the size of large data sets while maintaining integrity, thereby improving the ...

Handling missing data for unsupervised learning with an application on ...

Mathematics and Statistics Faculty Research & Creative Works (2020)

Louis Steinmeister, Dacosta Yeboah, Gayla Olbricht, Tayo Obafemi-Ajayi, et al.

"The problem of missing data and imputation have been widely discussed amongst specialists. However, many data scientists and applied statisticians ...

Structured Iterative Hard Thresholding For Categorical And Mixed Data Types

2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 (2019)

Thy Nguyen and Tayo Obafemi-Ajayi

In many applications, data exists in a mixed data type format, i.e. a combination of nominal (categorical) and numerical features. ...

Computational Learning Approaches to Data Analytics in Biomedical Applications, First ...

Mathematics and Statistics Faculty Research & Creative Works (2019)

Khalid Al-Jabery, Tayo Obafemi-Ajayi, Gayla Olbricht and Donald C. Wunsch

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine ...

Biomarker Discovery In Inflammatory Bowel Diseases Using Network-based Feature Selection

PLoS ONE (2019)

Mostafa Abbas, John Matta, Thanh Le, Halima Bensmail, et al.

Reliable identification of Inflammatory biomarkers from metagenomics data is a promising direction for developing non-invasive, cost-effective, and rapid clinical tests ...

Comparative Analysis Of Feature Selection Methods To Identify Biomarkers In ...

2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2019 (2019)

Thomas Clifford, Justin Bruce, Tayo Obafemi-Ajayi and John Matta

This paper applies machine learning feature selection techniques to the REGARDS stroke-related dataset to identify health-related biomarkers. A data-driven methodological ...

Genotype Combinations Linked To Phenotype Subgroups In Autism Spectrum Disorders

2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2019 (2019)

Junya Zhao, Thy Nguyen, Jonathan Kopel, Perry B. Koob, et al.

This paper investigates a computational model that allows for systematic comparison of phenotype data with genotype (Single Nucleotide Polymorphisms (SNPs)) ...

Multi-objective Optimization Approach To Find Biclusters In Gene Expression Data

2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2019 (2019)

Jeffrey Dale, Junya Zhao and Tayo Obafemi-Ajayi

Gene expression levels of organisms are measured by DNA microarrays. Finding biclusters in gene expression matrices provides invaluable information about ...