Moses E. Ekpenyong

Uyo, AK, Nigeria

Last Updated: 09/26/2026

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Found 8 publications

Developing an Explainable Artificial Intelligence System for the Mobile-Based Diagnosis of Febrile Diseases Using Random Forest, LIME, and GPT.

Developing an Explainable Artificial Intelligence System for the Mobile-Based Diagnosis of Febrile Diseases Using Random Forest, LIME, and GPT.

Journal: Healthcare informatics research
Published: January 10, 2025

A multimodal dataset for automating language vitality and endangerment assessment in south-south Nigeria.

A multimodal dataset for automating language vitality and endangerment assessment in south-south Nigeria.

Journal: Scientific data
Published: November 18, 2024

Enhancing the Interpretability of Malaria and Typhoid Diagnosis with Explainable AI and Large Language Models.

Enhancing the Interpretability of Malaria and Typhoid Diagnosis with Explainable AI and Large Language Models.

Journal: Tropical medicine and infectious disease
Published: August 07, 2024

Curating maternal, neonatal and child health (MNCH) datasets from a hospital's catchment area in Nigeria between 2014 and 2019.

Curating maternal, neonatal and child health (MNCH) datasets from a hospital's catchment area in Nigeria between 2014 and 2019.

Journal: F1000Research
Published: September 06, 2023

Collaborative Mining of Whole Genome Sequences for Intelligent HIV-1 Sub-Strain(s) Discovery.

Collaborative Mining of Whole Genome Sequences for Intelligent HIV-1 Sub-Strain(s) Discovery.

Journal: Current HIV research
Published: August 24, 2021

Processed HIV prognostic dataset for control experiments.

Processed HIV prognostic dataset for control experiments.

Journal: Data in brief
Published: April 21, 2021

A hybrid computational framework for intelligent inter-continent SARS-CoV-2 sub-strains characterization and prediction.

A hybrid computational framework for intelligent inter-continent SARS-CoV-2 sub-strains characterization and prediction.

Journal: Scientific reports
Published: April 01, 2021

Fuzzy-multidimensional deep learning for efficient prediction of patient response to antiretroviral therapy.

Fuzzy-multidimensional deep learning for efficient prediction of patient response to antiretroviral therapy.

Journal: Heliyon
Published: March 17, 2019
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Last Updated: 09/26/2026