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About myICD10
Our Mission
myICD10 exists to transform how healthcare professionals, patients, and technology teams interact with medical codes. We believe that by making these codes more accessible and searchable, we can drive greater transparency throughout the healthcare ecosystem.
Our goal is to build an intuitive platform where anyone—from patients deciphering medical bills to coders seeking references to developers building healthcare applications—can quickly find, understand, and utilize diagnosis and procedure codes without specialized training.
Our Story
myICD10 was born from a very practical challenge. While building predictive models at Pomelo Care to identify patients at risk for NICU admission, Evan encountered significant friction researching code meanings and communicating findings with clinical colleagues.
During weekend bike rides, Evan and Gareth discussed this persistent problem—the disconnect between technical and clinical understandings of medical codes. With Evan's healthcare implementation experience and Gareth's expertise in vector search technology at Pinecone, they recognized an opportunity to apply modern search techniques to revolutionize how people interact with medical coding systems.
What began as a conversation on wheels has evolved into a mission to make healthcare more transparent for everyone who needs to navigate the complex world of medical codes.
Meet the Team
Evan Sadler
Software Engineer
Machine learning engineer improving patient outcomes in healthcare. At Pomelo Care, Evan builds predictive models while tackling medical coding challenges. Previously at Warner Bros. Discovery, he orchestrated recommendation systems for HBO Max. Evan is also a founding engineer of Blue Rose Research.
Gareth Jones
Product Manager & Machine Learning Engineer
Product leader with deep technical foundations. At Pinecone, Gareth leads multiple product verticals powering vector search for AI applications. His accomplishments include co-founding ThirtyNine.ai (acquired by Labelbox) and building real-time machine learning systems at arturo.ai.
Our Approach & Future Direction
Beginning with foundational search capabilities, we're building a roadmap to incorporate increasingly sophisticated AI-powered search techniques. By leveraging advances in vector search and large language models, we aim to make medical code discovery more intuitive and contextually aware—transforming a traditionally frustrating experience into a seamless one.
Collaboration
We're actively working with physicians to address real-world pain points in medical code access and interpretation. As we bootstrap this initiative, we welcome input from all healthcare stakeholders. Please visit our contact page to learn how to connect with our team.