Our blog will be a forum for discussion – to tackle important issues in precision medicine and focus on how machine learning and artificial intelligence are being applied to improve health outcomes and lower the total cost of care. We’ll discuss topics like healthcare’s matching problem and how big ‘patient’ data can be used to discover which health interventions work for which patients. We’re excited to host this conversation.
While we don’t develop the drugs, or sell the health insurance plans, or treat patients, we work closely with health plans, biopharmaceutical companies, health systems, and patient foundations, to discover new knowledge that ultimately makes their care more precise and effective. Our major breakthrough in artificial intelligence, causal machine learning and simulation, is being applied to solve the most important problems in human health. In this blog, we’ll share stories of progress and the perspectives of our clients and partners, as we step by step make precision medicine a reality.
We are excited to discuss questions like:
- How can we scale precision medicine so that every patient is provided with personally optimized treatment plans?
- How can we turn data into models of disease progression and drug response so biomarkers can be discovered and drug development accelerated?
- How can we provide care managers and providers with insights that certain actions or interventions will have a greater impact versus other interventions for specific patients?
We have an amazing, dynamic team of PhDs, mathematicians, epidemiologists, computer scientists, physicists, geneticists, clinicians and business people at GNS and we will be using this blog as a vehicle to introduce them and their cutting-edge work as well as the work of our many partners and collaborators. This blog can be thought of as a journal of conversations with the broader GNS team (that you can join) and in the aggregate will tell the story of how to solve healthcare’s matching problem. You can expect us to publish to this blog weekly and deliver deeper dives into topics at least on a quarterly basis.
We’re also busy finding and sharing insights into these topics on social media. You can find us active on Twitter, Facebook and LinkedIn, so be sure to follow us today. And while you’re at it, be sure to subscribe to this blog, so you don’t miss a post.
Healthcare is incredibly complex and the potential of what machine learning – and especially causal machine learning – can do to better understand that universe is just starting to come into focus. We are pioneers mapping this new world and we invite you to join us on our journey through this blog and our social media posts.
Let’s have conversations about what needs to be done to improve healthcare outcomes, prevent and slow disease progression and reduce the cost of healthcare in the United States and around the world.
