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Chicago, IL, United States of America

Tempus Labs, Inc.

USPTO Granted Patents = 64

Trademarks = 25

Forward Citations = 376

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96 inventors (with patents filed for the assignee):

Aly Azeem Khan (15 out of 21 patents)

Hailey B Lefkofsky (11 out of 13 patents)

Caroline Epstein (10 out of 11 patents)

4. Stephen Yip (10 out of 15 patents)

5. Jonathan Ozeran (9 out of 16 patents)

6. Nike Tsiapera Beaubier (9 out of 9 patents)

7. Irvin Ho (9 out of 11 patents)

8. Lingdao Sha (9 out of 11 patents)

9. Boleslaw Osinski (9 out of 11 patents)

10. Ashraf Hafez (9 out of 11 patents)

11. Eric Lefkofsky (9 out of 14 patents)

12. Andrew J Kruger (7 out of 9 patents)

13. Michael Carlson (7 out of 9 patents)

14. Abel Greenwald (7 out of 9 patents)

15. Caleb Willis (7 out of 9 patents)

Core Competencies:

Biomarkers

Histopathology

Machine Learning

Cancer Diagnostics

Cardiac Event Prediction

Cohort Analysis

Metastasis Prediction

Liquid Biopsy

64 patents: Sort by Forward Citations

1. 12725682 - Systems, methods, and articles for imputing directed temporal measurements (2026-09-01),

2. 11935152 - Determining biomarkers from histopathology slide images (2024-03-19),

3. 11875903 - Method and process for predicting and analyzing patient cohort response, progression, and survival (2024-01-16),

4. 11869668 - Artificial intelligence based cardiac event predictor systems and methods (2024-01-09),

5. 11848107 - Predicting likelihood and site of metastasis from patient records (2023-12-19),

6. 11830587 - Method and process for predicting and analyzing patient cohort response, progression, and survival (2023-11-28),

7. 11769572 - Method and process for predicting and analyzing patient cohort response, progression, and survival (2023-09-26),

8. 11756688 - ECG-based cardiovascular disease detection systems and related methods (2023-09-12),

9. 11742064 - Automated quality assurance testing of structured clinical data (2023-08-29),

10. 11741365 - Generalizable and interpretable deep learning framework for predicting MSI from histopathology slide images (2023-08-29),

11. 11727674 - Systems and methods for generating histology image training datasets for machine learning models (2023-08-15),

12. 11715565 - Evaluating effect of event on condition using propensity scoring (2023-08-01),

13. 11715467 - Collaborative artificial intelligence method and system (2023-08-01),

14. 11705226 - Data based cancer research and treatment systems and methods (2023-07-18),

15. 11699507 - Method and process for predicting and analyzing patient cohort response, progression, and survival (2023-07-11),

Tempus Labs, Inc. is a technology company that utilizes artificial intelligence and machine learning to analyze large volumes of clinical and molecular data. Through their advanced data analytics platform, Tempus aims to revolutionize cancer care by providing physicians with actionable insights and personalized treatment options for their patients. With a mission to redefine how genomic data is used in a clinical setting, Tempus is dedicated to improving patient outcomes and accelerating research in the field of precision medicine.

This text is generated by artificial intelligence and may not be accurate.

Company Badge

USPTO Data Jan 1 1976 - Sep 29 2026

Tempus Labs, Inc.

64 Patents

#90 in Chicago, IL

#317 in Illinois

#5,677 in US

#11,463 in the World

Chicago, IL, United States of America

Tempus Labs, Inc.

Forward Citations = 376

96 inventors:

Aly Azeem Khan (15 out of 21 patents)

Hailey B Lefkofsky (11 out of 13 patents)

Caroline Epstein (10 out of 11 patents)

4. Stephen Yip (10 out of 15 patents)

5. Jonathan Ozeran (9 out of 16 patents)

Please report any incorrect information to [email protected]

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