For the Inventor, By the Inventor

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San Francisco, CA, United States of America

Enlitic, Inc.

USPTO Granted Patents = 74

% Expired Patents = 1.4

Trademarks = 2

Forward Citations = 423

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23 inventors (with patents filed for the assignee):

Kevin Lyman (74 out of 77 patents)

Li Yao (59 out of 60 patents)

Anthony Upton (52 out of 54 patents)

4. Ben Covington (51 out of 52 patents)

5. Eric C Poblenz (32 out of 32 patents)

6. Jordan Prosky (22 out of 22 patents)

7. Devon Bernard (18 out of 20 patents)

8. Lionel Lints (12 out of 12 patents)

9. Chris Croswhite (9 out of 9 patents)

10. Brian Basham (9 out of 9 patents)

11. Keith Lui (8 out of 8 patents)

12. Diogo Almeida (7 out of 7 patents)

13. Jeremy Howard (6 out of 6 patents)

14. Alan Liu (2 out of 7 patents)

15. Alexander Rhodes (2 out of 2 patents)

Core Competencies:

AI-Based Analysis

Medical Imaging

Scan Quality Assurance

Abnormality Detection

Multi-Model Analysis

Heat Map Generation

Artifact Detection

Medical Scan Triaging

Report Labeling

Patient Recruitment

Lesion Tracking

Image De-Identification

74 patents: Sort by Forward Citations

1. 12198085 - Artifact detection via a medical scan quality assurance system (2025-01-14),

2. 12061994 - Inference process visualization system for medical scans (2024-08-13),

3. 11922348 - Generating final abnormality data for medical scans based on utilizing a set of sub-models (2024-03-05),

4. 11829914 - Medical scan header standardization system and methods for use therewith (2023-11-28),

5. 11823106 - Location-based medical scan analysis system (2023-11-21),

6. 11810037 - Automatic patient recruitment system and methods for use therewith (2023-11-07),

7. 11790297 - Model-assisted annotating system and methods for use therewith (2023-10-17),

8. 11763933 - Medical report labeling system and method for use therewith (2023-09-19),

9. 11748677 - Multi-model medical scan analysis system using fine-tuned models (2023-09-05),

10. 11734629 - Medical scan labeling quality assurance system and methods for use therewith (2023-08-22),

11. 11694137 - Re-training a model for abnormality detection in medical scans based on a re-contrasted training set (2023-07-04),

12. 11694136 - Generating lesion change prediction data for medical scans (2023-07-04),

13. 11681962 - Peer-review flagging system and methods for use therewith (2023-06-20),

14. 11669965 - AI-based label generating system and methods for use therewith (2023-06-06),

15. 11669792 - Medical scan triaging system and methods for use therewith (2023-06-06),

Company Overview

Enlitic, Inc. is a San Francisco-based company specializing in advanced medical imaging solutions. The organization focuses on leveraging artificial intelligence to enhance the analysis of medical scans, ensuring improved accuracy in abnormality detection and scan quality assurance. Enlitic's innovative technologies encompass multi-model analysis, heat map generation, and artifact detection, facilitating efficient medical scan triaging. By integrating AI into medical imaging, Enlitic aims to transform diagnostic processes and improve patient outcomes.

Profile summary synthesized from public USPTO records and patent filings.

Company Badge

USPTO Data Jan 1 1976 - Oct 13 2026

74 Patents

#74 in San Francisco, CA

#1,172 in California

#4,976 in US

#10,131 in the World

San Francisco, CA, United States of America

Enlitic, Inc.

Forward Citations = 423

23 inventors:

Kevin Lyman (74 out of 77 patents)

Li Yao (59 out of 60 patents)

Anthony Upton (52 out of 54 patents)

4. Ben Covington (51 out of 52 patents)

5. Eric C Poblenz (32 out of 32 patents)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Enlitic, Inc.. Retrieved from https://idiyas.com/company/enlitic

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]

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