Machine Learning
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Tools for medicine, healthcare and HEOR research
Disease modeling and evidence-based decision support
We apply Bayesian networks and influence diagrams to support decision making under uncertainty and complexity.
We have experience in applications designed for:
- randomized clinical trials
- real-world datasets
- patient-reported outcomes
- population surveys
Features for health economics and outcomes research
- Prioritizing transparency, interpretability and the human-facing nature of analytics for health research
- Handling multiple outcomes, large or small dataset size and missingness in a unified model
- Incorporating subjective domain expertise
- Providing decision support under uncertainty for diagnosis and treatment plan selection
- Conducting causal and counterfactual analysis
- Supporting public education and dissemination of research
Personalized prognosis and health intelligence for precision medicine
We apply graphical models, probabilistic neural networks, random forests, influence diagrams and Markov process models
We provide solutions for problems in analytics to extract maximum value from:
- clinical trials and registries
- health insurance records
- electronic health records
- population surveys
Generated results
- Updatable, interpretable and scalable probabilistic models
- Combinable multiple formats and types of data
- Robust risk prediction and subgroup selection
- Multi-objective treatment plan selection models
- Incorporation of subjective values from the patient, physician and health insurer
- Value of information analyses and recommender systems
Biomedical signal processing
We work with convolutional/ recurrent neural networks, probabilistic graphical models and Markov process models
We work with firms and health systems on how to integrate data from:
- medical images
- patient registries
- hospitalization records
- electrocardiogram data
- wearables (pulse rate, sleep activity)
Features for analysis
- Time series, sequences (eg. waveform data) and images with a focus on interpretability and model criticism
- Automated medical diagnosis and disease management from point-of-care devices and smartphone-based sensors
- Anomaly detection in biomedical signals and clinical workflows to produce actionable insights for clinical decision support and intelligent monitoring systems research
Contact us
Canada
1 University Avenue. 3rd Floor.
Toronto, Ontario.
M5J 2P1. Canada
1-800-535-9760
Inquiries
info@lighthouseoutcomes.com