Active Research Projects
Search, filter, and inspect C-MAC Ghana’s computational research projects, deep learning medical models, and precision agricultural telemetry systems.
Multi-Architecture CNN for Anemia Screening
Deep learning model utilizing conjunctival micro-vasculature imagery for real-time pediatric iron deficiency screening.
Predictive Analytics
Creating machine learning models to predict disease progression and treatment outcomes.
Secure Health Data Infrastructure
Designing compliant, offline-first database systems for rural health centers.
Precision Agriculture
IoT-based systems for real-time monitoring of soil conditions, weather patterns, and crop health.
Crop Disease Detection
Computer vision algorithms for early identification of plant diseases using mobile devices.
Yield Prediction
Machine learning models to predict crop yields based on historical data and environmental factors.
No research papers found
Try searching with a different keyword or switching categories.
Research Collaborations
Partnering with leading institutions for greater impact
Koforidua Technical
University
Computer Science Department
Ghana Communications
Technology University
Computer Science Department
Methodist University Ghana -
Accra
Department of I.T and Mathematical Sciences
Research Impact & Outcomes
Transforming research into real-world solutions
Healthcare Impact
AI diagnostic tools deployed in 10+ healthcare facilities, improving early disease detection by 40%
Agricultural Impact
Smart farming solutions increasing crop yields by 35% for 500+ smallholder farmers
Capacity Building
Training 200+ African researchers in AI and data science methodologies
Innovation Labs & Infrastructure
State-of-the-art facilities driving groundbreaking research
AI Research Lab
- NVIDIA DGX Systems
- High-Performance Computing Cluster
- Medical Imaging Workstations
Data Science Center
- Big Data Analytics Platform
- Cloud Computing Infrastructure
- Data Visualization Tools
Recent Publications
Explore the latest findings and technical reports published by Dr. Justice Williams Asare and the C-MAC Ghana team.
A Smartphone and Web‐Based Automated Platform for Segmenting Urinary Tract Infection Using a Deep Learning‐Based Approach
Developing an accessible mobile application backed by advanced deep learning techniques to rapidly and accurately diagnose urinary tract infections.
A hybrid three-layer convolutional neural network architecture for detecting anemia using clinical images
Proposing a novel, highly accurate CNN architecture designed for the rapid classification and non-invasive detection of anemia using standard clinical imaging.
Application of artificial intelligence for okra leaf and other plant disease detection and diagnoses: a systematic literature review
A comprehensive review of how modern AI and computer vision models are transforming early disease detection in agricultural settings.
Application of machine learning approach for iron deficiency anaemia detection in children using conjunctiva images
Evaluating machine learning pipelines that analyze eye conjunctiva images to estimate hemoglobin levels and detect anemia without invasive blood tests.
Iron deficiency anemia detection using machine learning models: A comparative study of fingernails, palm and conjunctiva of the eye images
A comparative study analyzing different bodily features to determine the most effective visual indicators for machine-learning-based anemia screening.