Salt Lake City, UT, United States of America

William Paul Bone

USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations of William Paul Bone

Introduction

William Paul Bone is an accomplished inventor based in Salt Lake City, UT. He has made significant contributions to the field of clinical-phenomics through his innovative patent. His work focuses on utilizing advanced machine learning techniques to analyze gene perturbation data and clinical outcomes.

Latest Patents

William Paul Bone holds a patent titled "Utilizing a clinical-phenomics causal discovery framework to generate causal discovery predictions." This patent involves systems, non-transitory computer-readable media, and methods that analyze gene perturbation machine learning embeddings and clinical observation data sets. The technology aims to generate causal predictions between genes and clinical outcomes by employing machine learning, explainability models, and causal discovery models. His patent is a testament to his expertise in the intersection of genetics and machine learning, with a focus on identifying gene targets and generating causal predictions.

Career Highlights

William Paul Bone is currently associated with Recursion Pharmaceuticals, Inc., where he applies his innovative ideas to advance the field of pharmaceuticals. His work at Recursion Pharmaceuticals emphasizes the importance of integrating machine learning with clinical data to improve healthcare outcomes. With a patent portfolio that includes 1 patent, he continues to push the boundaries of what is possible in clinical research.

Collaborations

William collaborates with talented professionals in his field, including his coworker Hayley Jeton Donnella. Their combined expertise contributes to the innovative projects at Recursion Pharmaceuticals, fostering an environment of creativity and scientific advancement.

Conclusion

William Paul Bone is a notable inventor whose work in clinical-phenomics and machine learning is paving the way for future innovations in healthcare. His contributions are significant, and his patent reflects his commitment to improving clinical outcomes through technology.

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