Lymphoma Prediction
Personalized treatment
Scalable solution
Global application
The challenge
Driving personalized pet healthcare through asynchronous data
The pet care industry is under growing pressure to deliver personalized, effective treatments due to the wide variety of breeds and health conditions. With over 300 dog breeds and 70+ cat breeds, accurate and comprehensive data is essential, driving the demand for innovative solutions that leverage asynchronous pet data for improved healthcare outcomes.
Key challenges
Personalized care requires analyzing unique symptoms
Breed diversity complicates therapy response
Cancer drug dosage impacts life expectancy
The solution
AI-driven solution for personalized pet oncology
Oncology research
Analyzed pet oncology studies
Gathered critical treatment insights
Identified key factors in feline lymphoma
Predictive AI algorithms
Developed treatment recommendation system
Applied advanced machine learning models
Personalized care for each pet
Implementation approach
1
Pet360
Centralized pet data
Captures health, prescriptions, diagnostics
Enables comprehensive analysis
2
Survival analysis
Kaplan-Meier curves
Predicts survival duration
Assesses treatment effectiveness
3
Lymphoma prediction
CatBoost algorithm
SHAP analysis for key drivers
Uses 80+ features for prediction
The impact
Comprehensive insights for enhanced treatment effectiveness
Predict lymphoma occurrence
Assess treatment effectiveness
Generate personalized survival predictions
Looking ahead
Expanding reach
Broaden the solution to include more species
Data integration
Integrate new health data for better insights
Enhanced predictions
Continuously improve treatment predictions and outcomes
