Grace Oluchi Diri

Integrative Machine Learning Framework for Predicting Heart Disease from Multivariate Cardiovascular Risk Profiles

Ezekiel Ebere Diri, Kingsley Theophilus Igulu, Grace Oluchi Diri, Emmanuel Aburuotu et autres

gb, Nigéria (code pays fourni par la source)

Optimising Stroke Recurrence Prediction Using Minimal Clinical Features and Machine Learning Models

Ezekiel Ebere Diri, Grace Oluchi Diri, Rita Chikeru Owhonda, Lebari Goodday Nbaakee et autres

Stroke recurrence remains one of the most devastating challenges in managing cerebrovascular disease, adding to disability, mortality, and rising healthcare costs worldwide. Being able to predict recurrence early could mean the difference between timely intervention and irreversible outcomes. In this study, we …

nl, gb (code pays fourni par la source)

Behavioural Analysis and Churn Forecasting in Retail Banking Using Machine Learning Models

Ezekiel Ebere Diri, Grace Oluchi Diri, Kyle Elliot, Rita Chikeru Owhonda et autres

This research investigates the use of machine learning techniques to forecast customer churn in retail banking. We worked with a dataset containing demographic, financial, and behavioural attributes for approximately 10,000 customers. To model churn risk, we trained and tested three classifiers: Gradient …

gb (code pays fourni par la source)

Comparative Study of Sentiment Analysis Techniques: Traditional Machine Learning vs. Deep Learning Approaches

Grace Oluchi Diri, Philip Obiorah, Hongbo Du

Aim/Purpose This paper presents a comparative analysis of sentiment classification models, focusing on the performance differences between lexicon-based sentiment analysis, traditional machine learning techniques, and transformer-based deep learning approaches across multiple benchmark datasets. Background While numerous methods exist for sentiment analysis, a …

gb (code pays fourni par la source)

Electrocardiographic and Biochemical Feature Integration for Automated Cardiovascular Risk Stratification

Grace Oluchi Diri, Ezekiel Ebere Diri, Lebari Goodday Nbaakee, Kingsley Theophilus Igulu

This work explored how machine learning can help identify patients with Congestive Heart Failure (CHF) using both ECG readings and biochemical test results. The dataset included 1,000 patient records with structured features from lab reports, ECG intervals, clinical signs, and diagnostic history. …

Hybridized Feature Extraction for Facial Age Estimation using SVM

Grace Oluchi Diri

Forging of age is increasing dramatically these days, especially in areas such as military, industry, crime, processing of visa, job application, etc.One of the areas of human-PC-interaction is developing an application for the automated estimation of age using face pictures.Typically, an age …