Philadelphia, PA, United States of America

Eamon Caddigan

USPTO Granted Patents = 2 

Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2024

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2 patents (USPTO):Explore Patents

Title: Eamon Caddigan: Innovator in Health Prediction Technology

Introduction

Eamon Caddigan is a notable inventor based in Philadelphia, PA, who has made significant contributions to the field of health prediction technology. With a focus on machine learning and wearable devices, Caddigan's work aims to enhance the understanding and management of acute health conditions.

Latest Patents

Caddigan holds 2 patents, with his latest invention being a sensor-based machine learning system designed for health prediction. This innovative system analyzes datasets from users who report symptoms, alongside data collected from wearable devices. It aims to measure the impact of acute health conditions, such as the flu, at a population level. The machine learning model developed by Caddigan can recognize individual health condition patterns based on user activity and baseline characteristics. By aggregating normalized changes at the population level, the system can predict the onset of certain acute health conditions and implement interventions to manage their impact on individuals.

Career Highlights

Caddigan is currently employed at Evidation Health, Inc., where he continues to develop and refine his innovative health prediction technologies. His work is pivotal in bridging the gap between technology and healthcare, providing valuable insights into population health management.

Collaborations

Caddigan collaborates with talented professionals in his field, including Luca Foschini and Raghunandan Melkote Kainkaryam. These collaborations enhance the development of cutting-edge solutions in health prediction.

Conclusion

Eamon Caddigan's contributions to health prediction technology through his innovative patents and collaborations position him as a key figure in the intersection of machine learning and healthcare. His work has the potential to significantly impact how acute health conditions are managed at both individual and population levels.

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