AI Solution for Embryo Quality Prediction
Business Problem
Implementing an AI-based system to enhance embryo quality prediction in assisted reproductive technologies (ART), reducing human errors, streamlining doctor workflows, and improving the precision of embryo classification to increase the likelihood of successful pregnancies.
Objectives
- Maximize Embryo Selection Accuracy: Improve the precision of embryo classification to increase the success rate of ART procedures.
- Minimize Treatment Cost: Ensure the solution is cost-effective and reduces overall treatment expenses.
Success Criteria
1. Success Criteria
Increase the success rate of ART procedures.
2. ML Success Criteria
Achieve an accuracy greater than 75% in embryo quality prediction.
3. Economic Success Criteria
Achieve cost savings of at least 25% by reducing the expenditure on working with embryos of lower viability.
Key Features
- Automated Embryo Classification: Utilize AI to classify embryo quality with high accuracy.
- Error Reduction: Minimize human errors in the embryo selection process.
- Workflow Streamlining: Enhance doctor workflows to improve efficiency and effectiveness.
Benefits
- Improved Accuracy: High precision in predicting embryo quality.
- Increased Success Rates: Higher likelihood of successful pregnancies through better embryo selection.
- Cost Efficiency: Reduced treatment costs and minimized expenditure on lower viability embryos.