You will get Diphtheria Outbreak Prediction System
Project details
You will get a high-precision AI system that predicts diphtheria outbreaks with 90%+ accuracy, enabling early intervention and saving lives. With my background in both engineering and medical AI, I deliver robust, scientifically-validated models that integrate seamlessly into healthcare workflows. I've successfully built predictive systems analyzing 3,500+ clinical records, achieving 92% accuracy in outbreak forecasting. My approach combines rigorous data science with practical healthcare applications, ensuring your system is both technically sound and medically useful.
Machine Learning Tools
Google Data Studio, Microsoft Excel, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SQL, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$1,000
|
Standard
$3,500
|
Advanced
$6,000
|
|---|---|---|---|
| Delivery Time | 15 days | 20 days | 30 days |
Number of Revisions | 2 | 4 | 6 |
Number of Graphs/Charts | 7 | 10 | 15 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$250 - $500
Additional Graph/Chart
(+ 3 Days)
+$50Frequently asked questions
About Femi
Full-stack developer || Machine learning engineer || web & App Design
Lagos, Nigeria - 3:37 am local time
My expertise includes:
Full Stack Development with Django, React, Node.js, and REST APIs
Machine Learning & AI using PyTorch, TensorFlow, and Scikit-learn
Computer Vision for automated detection and analysis (OpenCV, CNNs)
DevOps & Deployment with CI/CD, and GitHub Actions
Project Leadership & Technical Training
I have successfully delivered projects ranging from educational platforms and fintech solutions to AI-powered medical and infrastructure systems. I am passionate about creating efficient, secure, and scalable digital solutions that drive real-world impact.
Let’s collaborate to turn your ideas into robust, high-performance software.
Steps for completing your project
After purchasing the project, send requirements so Femi can start the project.
Delivery time starts when Femi receives requirements from you.
Femi works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1: Medical Data Analysis & Requirements
Analyze available clinical datasets (3,500+ records) Consult with medical experts on prediction parameters Define prediction accuracy targets (90%+) Document data privacy and ethical considerations
Data Engineering & Preprocessing
Clean and normalize medical dataset Handle missing values and outliers Perform feature engineering for predictive power Split data into training, validation, and test sets Create reproducible data processing pipeline