• Recent
  • Class
  • Inventors
  • Assignees
  • Top Lists
  • Pricing
  • Account
Patents-Review.com
  1. Home
  2. Inventor
  3. C
  4. Chu…
  5. Chung Nancy Ling
🔗 Permalink
Inventor profile of:

Nancy Ling Chung

City:

Edgewater, Maryland

Country:

United States

Published Applications:

9

Last publication date:

2025-09-11

Recent patent applications by Chung Nancy Ling

Nancy Ling Chung from Edgewater, US has applied for patents for these inventions. The list has both pending applications and granted patents:

#1 | 2025-09-11
US20250281298A1
Human necessities

PAPILLARY MUSCLE APPROXIMATION

#2 | 2025-09-11
US20250281297A1
Human necessities

VENTRICLE TETHERING

#3 | 2025-06-12
US20250186209A1
Human necessities

ECHOGENIC SUTURES FOR CARDIAC PROCEDURES

#4 | 2025-01-30
US20250032256A1
Human necessities

SUPPORT DEVICE FOR VALVE LEAFLET

#5 | 2024-11-07
US20240366382A1
Human necessities

METHODS AND DEVICES FOR HEART VALVE REPAIR

#6 | 2024-11-07
US20240366378A1
Human necessities

ADJUSTABLE ANNULOPLASTY DEVICE

#7 | 2024-10-17
US20240341744A1
Human necessities

MINIMALLY-INVASIVE DEFECT CLOSURE

#8 | 2024-05-30
US20240173034A1
Human necessities

CLIP AND METHOD FOR CLOSING LEFT ATRIAL APPENDAGE

#9 | 2024-02-22
US20240058034A1
Human necessities

MULTI-LUMEN CARDIAC ACCESS

InventorID:

6070892 ⎘

  1. Home
  2. Inventor
  3. C
  4. Chu…
  5. Chung Nancy Ling

Some parts © 2022-2026 Patents-Review.com

Browse & Discovery
  • Home
  • Patent Classification
  • Inventor Index
  • Assignee Index
  • Interesting Applications
Search & Tools
  • Basic Search
  • Advanced Search
  • Patent Alerts
  • Top Lists
  • Statistics
Information & Resources
  • About US Patent System
  • Terms & Privacy
  • Pricing
  • Contact
Quick Access
  • Latest Applications
  • Top Inventors 2026
  • Top Assignees 2026
  • Featured Patents
Disclaimer: This website is intended for informational purposes only, and its content is based on public patent records. Please note that some sections of this website have been created or processed using machine learning models. We provide content in good faith but make no guarantees regarding accuracy or completeness. By using this site, you accept any risks and waive claims against us for errors or omissions.