Los Angeles, CA, United States of America

Daniel Lee Ruderman

USPTO Granted Patents = 3 

Average Co-Inventor Count = 4.3

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023-2025

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3 patents (USPTO):

Title: Inventor Spotlight: Daniel Lee Ruderman

Introduction

Daniel Lee Ruderman, based in Los Angeles, CA, is an accomplished inventor known for his significant contributions in the field of digital pathology. With a total of three patents to his name, Ruderman is at the forefront of innovative technologies that harness machine learning to advance cancer medicine.

Latest Patents

One of Ruderman's latest patents focuses on histopathology classification through machine self-learning of 'tissue fingerprints'. This groundbreaking work aims to enhance the efficiency of cancer medicine by improving the identification of individual tumors through a learned set of histologic features. In this patent, he introduces a novel algorithm that operates independently of image metadata annotations, successfully matching hematoxylin and eosin stained tissues to patient specimens with impressive accuracy of 93%. Additionally, his research includes the development of a fingerprint-based classifier capable of predicting the molecular status of tumors, specifically breast cancer clinical estrogen receptor status, with a high area under the receiver operating characteristic curve (AUROC) of 0.90. This innovation paves the way for machine learning algorithms that significantly improve clinical decision-making in patient management.

Career Highlights

Daniel Lee Ruderman is associated with the University of Southern California, a leading research institution where he continues to innovate at the intersection of technology and medicine. His work not only highlights his ability as a skillful inventor but also showcases his commitment to enhancing the tools available for cancer diagnosis and treatment.

Collaborations

Throughout his career, Ruderman has collaborated with esteemed colleagues, including David B Agus and Rishi Raghav Rawat. These partnerships reflect a shared vision of leveraging technology to improve healthcare outcomes through innovative research and development in digital pathology.

Conclusion

Daniel Lee Ruderman's contributions to the field of histopathology through his innovative patents exemplify the potential of machine learning to transform cancer medicine. His work not only enhances diagnostic accuracy but also supports the development of new algorithms that provide crucial information for patient management. As he continues to innovate, Ruderman stands as a vital figure in the ongoing evolution of healthcare technology.

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