Yaron is the VP Engineering at Causalis.ai. Introduced to the company by a friend, he was sufficiently intrigued by Causalis.ai’s technology to join the team and apply his 23 years of development experience to revolutionizing the world of healthcare.
“Our goal at Causalis.ai is to reduce suffering and maximize clinical outcomes on a global scale using our technology. We aim to achieve this by developing a platform that will allow machine learning to teach itself to identify causal relationships within data.
The Causalis.ai platform will help both oncologists and patients determine their optimal patient-specific treatment for lung cancer. This will empower all relevant parties to make an informed decision about how to deal with this particularly aggressive form of cancer and optimize treatment when considering factors such as potential side effects, life expectancy, and quality of life.”
The StarFinder Lab Experience
After three months in the program as part of the StarFinder Lab first cohort, it has far exceeded my expectations. The ability to access data that would’ve been either too costly or simply inaccessible if not for Roche removes a significant barrier that startups like ourselves experience. The input and guidance from healthcare professionals with insider knowledge as to where our technology is best applied, along with the extensive business experience of aMoon and their ability to help us understand what our company needs and its potential weaknesses have all been invaluable to us.”
In fact, the combination of Roche and aMoon amounts to a perfect holistic fit of diagnostic, industry, and business advice: saving us time and money while positioning us for success.”