Causālis
Powering Precision Medicine via Causal AI
About Us
Causalis is seeking to address a global challenge in chronic conditions treatment: finding the optimal balance between efficacy and tolerance in the treatment of patients prior to starting the treatment. Our team is developing a robust Causal AI platform. Our causal AI platform can analyze and discover the causal & effects relationships between individual clinical, lifestyle, and omics data.
Causal AI
While traditional AI methods learn correlation patterns, and by that at best learn how to repeat previous practice, using the mathematics of causal inference, our proprietary AI derives the mechanisms underlying your data to produce cause-effect insights.
Data Fusion
Data in challenging domains such as healthcare is often noisy, sparse, and from mixed sources and different modalities. Our advanced data engineering and infrastructure handles these challenges seamlessly, transparently, and securely.
Decisions Intelligence
Following previous practice or gut feeling is suboptimal. Our solutions provide data-driven, cause-and-effect reasoning to compare potential futures and choose the optimal course of action: If I take this action today, what will be the outcome tomorrow?
"Deep learning is good at finding patterns in realms of data, but can't explain WHY they're connected"
Yoshua Bengio
Our Team
In our initial offering, we are developing a platform that will allow clinicians to make a decision hand-in-hand with patients, taking into consideration the patient's prioritization regarding life expectancy and adverse events. We are a group of multi-disciplinary individuals with diverse backgrounds, collaborating with leading medical centers and data providers globally, to further develop our offering.
