Optimizing Your CMS for Performance

Background

I’m 10 years into building healthcare technology companies, previously the Founder and CEO of Biofourmis. I set out on a mission 10 years ago to harness the power of data and technology to bring the right care to every person, no matter where they are. My sole focus now is OutcomesAI. My ambition is to build this company with a 10-year view, spending my time and resources to build a safe AI for healthcare.

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The company

I believe that providing safe, accessible, engaging, and personalized healthcare is the moral priority of our time. The most meaningful impact will come from technologies that enable delivery of high-quality healthcare at-scale. In the coming ages we will see great advancements in general-purpose Artificial Intelligence (AI) performing at expert-level. By contributing to the early-stage development, we can set the course for a safe medical AI future for humanity.

Hence the goal of OutcomesAI: to develop specialized and safe Artificial Medical Intelligence (AMI) to supercharge healthcare teams, and provide engaging and personalized care to patients, all for better clinical outcomes.

Our company journey will take time and will require a championship team dedicated to the mission, deep clinical collaborations, and AI engineering innovation to achieve a mass-market impact and adoption. We will face risks, safety concerns, and adoption challenges. However, if we succeed, we will make a positive impact on healthcare and build the largest medical AI company on the planet.

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How we can do it

I’m 10 years into building healthcare technology companies, previously the Founder and CEO of Biofourmis. I set out on a mission 10 years ago to harness the power of data and technology to bring the right care to every person, no matter where they are. My sole focus now is OutcomesAI. My ambition is to build this company with a 10-year view, spending my time and resources to build a safe AI for healthcare.

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1. Artificial Medical Intelligence (AMI):
   Unlike other models which are built for singular data types – our team is focused on building a multi-modal foundation model (using text, audio, images, sensor signals) for healthcare applications – ensuring safety and clinical performance by pre-training on trusted clinical data and fine-tuning using human feedback.
2. Care Delivery Operating System:
   We aim to augment the entire patient journey from diagnosis, treatment to follow-up care, handling administrative and clinical tasks and providing timely clinical decision support for clinicians. A fully workflow-integrated system is required on which clinical tasks operate and information flows. To achieve this goal, we distill best practices and efficient clinical workflows, integrate up-to-date evidence and guidelines, and redesign processes for personalized care, all into a single operating system powered by our AI, providing unified and seamless user experience.