AuxilioMD is an integration platform that helps researchers set up a clinical validation study by providing the front and backend software to pilot their models in a hospital. We are the last-mile solution for clinical researchers who want to validate, implement, and eventually sell their machine learning (ML) models for healthcare diagnostics.
Here, we present you our open source project. Check out our GitHub!
We partnered with Dr. Shung, who developed a ML-algorithm to risk triage upper GI bleeding patient to conduct our first case study.
Upper GI bleeding is a prominent problem in all age groups, by using machine learning, patients can be better supported in the diagnosis process.
To read more on his algorithm, and how it will benefit the future of clinical decision tools, click the button bellow!
You will get to know more about us -- our history, the challenges we faced, and why we are committed to our work with AuxilioMD.
AuxilioMD will help you build a machine learning diagnostic tool that is connected to the hospital's EHR system and seamlessly integrate into doctors' workflow.
AuxilioMD will run through machine learning models to generate visual diagnostics and risk scores that doctors can effectively use to treat patients.
AuxilioMD provides personalized support that will help you develop a tool that fully satisfy your needs.
We are a team of five ambitious Yale undergraduates and two extraordinary Yale New Haven Hospital physicians. Together, we tackle the problems in health care and provide innovative machine learning solutions.
Got any questions? Don't hesitate to reach out to our team.