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Dr. Nisheeth Pandey, MD
Dr. Nisheeth Pandey, MD
Pain Management Specialist, New York Spine Specialist (Bronx, NY)
Bachelor of Arts, University of Virginia
Dr. Nisheeth Pandey has 5 years of experience in the fields of Anesthesiology and Pain Medicine. He earned his BA in Economics and Finance from the University of Virginia and his MD from the Icahn School of Medicine at Mount Sinai. After completing a residency in Anesthesiology at NewYork-Presbyterian/Columbia University Irving Medical Center, he went on to complete a fellowship in Pain Management at the Icahn School of Medicine at Mount Sinai. Today, this expert is board certified in Anesthesiology and Pain Medicine. Formerly, this expert served as the Owner of Panda Productions, Inc., where he also served as an Attending Physician. He was also a Pain Management Specialist with Pain Management Group and an Anesthesiologist at OhioHealth Berger Hospital. He currently serves as a Pain Management Specialist for New York Spine Specialist.
(516) ***-****
Brooklyn, New York
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Radar Metrics At A Glance
Expert Witness Activity
Plaintiff Cases
Defense Cases
Expert Challenges
Deposition Transcripts
Publications
63
Media & News
30
Social Media Mentions
Expert Witness Activity
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Litigation Analytics
Retained By
Defense
Plaintiff
Activity over time
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2000
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Activity by state
Case Outcome
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Education
Institution | Degree Type |
|---|---|
University of Virginia | Bachelor of Arts |
Icahn School of Medicine at Mount Sinai | Doctor of Medicine |
Work History
Title | Employer |
|---|---|
Pain Management Specialist | New York Spine Specialist (Bronx, NY) |
Owner/Attending Physician | Panda Productions, Inc. (Columbus, OH) |
— | Icahn School of Medicine at Mount Sinai (New York, NY) |
Publications
Radar found 63 records
Title | Type |
|---|---|
Security issues and challenges in cloud of things-based applications for industrial automation | Journal Article |
Multi-Faceted Job Scheduling Optimization Using Q-learning With ABC In Cloud Environment | Journal Article |
World Coin Currency Detection: A Comparative Study of Machine Learning and Deep Learning | Conference Proceeding |
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