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Jonathan A Forsberg

from Berkeley, CA
Age ~52
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Also known as:
Jonathan Agner Forsberg, Jonathan N Forsberg, Johnathan A Forsberg, Jon Forsberg, Jonathan Agner
Related to:
Marilyn A Forsberg, 34Allyson Forsberg, 62Ruth KassLouis Kass
Connected to:
Ben W Forsberg, 33Brady S Forsberg, 39Cheryl S Forsberg, 81Corey R Forsberg, 62David D Forsberg, 71Jerald L Forsberg, 80Joanna P Forsberg, 92Josef D Forsberg, 46Laura N Forsberg, 53Mariana Forsberg, 50

Jonathan Forsberg Phones & Addresses

  • Berkeley, CA
  • 3814 Everett St, Kensington, MD 20895 (301) 718-9530 (301) 962-0999 (301) 951-1866
  • New York, NY
  • 875 Coachway, Annapolis, MD 21401 (410) 841-2434 (410) 841-6264 (410) 849-2743
  • 8813 Hawkins Ln, Chevy Chase, MD 20815 (301) 718-9530 (301) 951-1866
  • Whitefish, MT
  • 8813 Hawkins Ln, Chevy Chase, MD 20815

Work

Company: Walter Reed Orthopedic Clinic Address: 8901 Wisconsin Ave Suite 19, Bethesda, MD 20889 Phones: (301) 319-4428

Education

School / High School: Uniformed Services University of The Health Sciences 2001

Languages

English

Specialities

Orthopedic Surgery

Professional Records

License Records

Jonathan A Forsberg

Address:
3814 Everett St, Kensington, MD
807 Children's Way, Jacksonville, FL
License #:
8534 - Expired
Category:
Health Care
Issued Date:
Jan 3, 2005
Effective Date:
Aug 16, 2011
Expiration Date:
Jan 3, 2007
Type:
Registration for Resident/HSE Physician

Medicine Doctors

Jonathan Forsberg Photo 1

Dr. Jonathan A Forsberg, Bethesda MD - MD (Doctor of Medicine)

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Specialties:
Orthopedic Surgery
Address:
Walter Reed Orthopedic Clinic
8901 Wisconsin Ave Suite 19, Bethesda, MD 20889
(301) 319-4428 (Phone)
Languages:
English
Education:
Medical School
Uniformed Services University of The Health Sciences
Graduated: 2001
Jonathan Forsberg Photo 2

Jonathan A. Forsberg

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Specialties:
Orthopaedic Surgery
Work:
Walter Reed National Medical Center Orthopedic Clinic
8901 Wisconsin Ave, Bethesda, MD 20889
(301) 319-4428 (phone), (301) 295-4141 (fax)

Walter Reed Med Ctr Orthopedics
8901 Rockville Pike, Bethesda, MD 20889
(301) 295-4290 (phone), (301) 295-2284 (fax)
Education:
Medical School
Uniformed Services University of the Health Sciences Hebert School of Medicine
Graduated: 2001
Conditions:
Osteoarthritis
Languages:
English
Spanish
Description:
Dr. Forsberg graduated from the Uniformed Services University of the Health Sciences Hebert School of Medicine in 2001. He works in Bethesda, MD and 1 other location and specializes in Orthopaedic Surgery. Dr. Forsberg is affiliated with Walter Reed National Military Medical Center.
Jonathan Forsberg Photo 3

Jonathan Agner Forsberg, Bethesda MD

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Specialties:
General Practice
Orthopaedic Surgery
Geriatric Medicine
Work:
National Naval Medical Center
8901 Wisconsin Ave, Bethesda, MD 20089
Education:
Uniformed Services University (2001)
Jonathan Forsberg Photo 4

Jonathan Agner Forsberg, Bethesda MD

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Specialties:
Orthopedic Surgeon
Address:
8901 Wisconsin Ave, Bethesda, MD 20889

Public records

Vehicle Records

Jonathan Forsberg

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Address:
3814 Everett St, Kensington, MD 20895
Phone:
(301) 962-0999
VIN:
JTJHW31U072008048
Make:
LEXUS
Model:
RX 400H
Year:
2007

Business Records

Name / Title
Company / Classification
Phones & Addresses
Jonathan Agner Forsberg
Jonathan Forsberg MD
Orthopedics
8901 Rockville Pike, Bethesda, MD 20889
(301) 295-0730

Publications

Us Patents

Clinical Decision Model

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US Patent:
20110289035, Nov 24, 2011
Filed:
Apr 8, 2011
Appl. No.:
13/083090
Inventors:
Alexander Stojadinovic - Chevy Chase MD, US
Eric Elster - Kensington MD, US
Doug K. Tadaki - Frederick MD, US
Trevor Brown - Washington DC, US
Thomas A. Davis - Oak Hill VA, US
Jonathan Forsberg - Kensington MD, US
Jason Hawksworth - Silver Spring MD, US
International Classification:
G06N 5/00
G06F 17/00
US Classification:
706 45
Abstract:
An embodiment of the invention provides a method for determining a patient-specific probability of disease. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of the healing rate of an acute traumatic wound is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of the healing rate of an acute traumatic wound.

Clinical Decision Model

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US Patent:
20110289036, Nov 24, 2011
Filed:
Apr 8, 2011
Appl. No.:
13/083184
Inventors:
Alexander Stojadinovic - Chevy Chase MD, US
Eric A. Elster - Kensington MD, US
Doug K. Tadaki - Frederick MD, US
Trevor Brown - Washington DC, US
Thomas A. Davis - Oak Hill VA, US
Jonathan Forsberg - Kensington MD, US
Jason Hawksworth - Silver Spring MD, US
Roslyn Mannon - Birmingham AL, US
International Classification:
G06N 5/00
G06F 17/00
US Classification:
706 45
Abstract:
An embodiment of the invention provides a method for determining a patient-specific probability of transplant glomerulopathy. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of transplant glomerulopathy is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant glomerulopathy.

Clinical Decision Model

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US Patent:
20110295782, Dec 1, 2011
Filed:
Oct 15, 2009
Appl. No.:
13/123406
Inventors:
Alexander Stojadinovic - Chevy Chase MD, US
Eric A. Elster - Kensington MD, US
Doug K. Tadaki - Frederick MD, US
Trevor S. Brown - Washington DC, US
Thomas A. Davis - Oak Hill VA, US
Jonathan Forsberg - Kensington MD, US
Jason Hawksworth - Silver Spring MD, US
Roslyn Mannon - Birmingham AL, US
Aviram Nissan - Aviram-Yehuda, IL
International Classification:
G06F 15/18
US Classification:
706 12
Abstract:
An embodiment of the invention provides a method for determining a patient-specific probability of disease. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of disease.

Orthopaedic Fixation Assembly, System, And Method Of Use

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US Patent:
20210137563, May 13, 2021
Filed:
Jan 25, 2021
Appl. No.:
17/156973
Inventors:
- Kensington MD, US
Jonathan A. FORSBERG - Kensington MD, US
Assignee:
The Solsidan Group, LLC - Kensington MD
International Classification:
A61B 17/64
A61B 17/74
A61F 2/78
Abstract:
An orthopaedic fixation assembly for prosthetic biologic attachment. The orthopaedic fixation assembly may include a main body with a longitudinally-extending stem having a proximal end, a distal end, and a cavity body. An anchor plug may be configured to be received within the stem cavity, and securable thereto via complementary mating surfaces. A spindle structure may be fixedly attached to the proximal end of the longitudinally-extending stem and protrude outwardly therefrom such that a portion of the structure extends externally beyond the resected cavity of the bone that may prevent rotational motion of the spindle. The spindle structure may have at least one compliant biasing member configured to apply a compressive force to the surrounding bone. A porous coating may be at the juncture between stem and spindle structure, on the spindle, and the splines and anti-rotation chocks, improving the initial stability of the implant and facilitating long-term bone ingrowth.

Clinical Decision Model

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US Patent:
20200335179, Oct 22, 2020
Filed:
Jul 7, 2020
Appl. No.:
16/923014
Inventors:
- Arlington VA, US
- Fort Detrick MD, US
Trevor Brown - Washington DC, US
Thomas A. Davis - Oak Hill VA, US
Jonathan Forsberg - Kensington MD, US
Jason Hawksworth - Silver Spring MD, US
International Classification:
G16B 40/00
Abstract:
An embodiment of the invention provides a method for determining a patient-specific probability of disease. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of the healing rate of an acute traumatic wound is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of the healing rate of an acute traumatic wound.

Orthopaedic Fixation Assembly, System, And Method Of Use

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US Patent:
20190038317, Feb 7, 2019
Filed:
Aug 1, 2018
Appl. No.:
16/051732
Inventors:
- Kensington MD, US
Jonathan A. FORSBERG - Kensington MD, US
Assignee:
The Solsidan Group, LLC - Kensington MD
International Classification:
A61B 17/64
A61B 17/74
A61B 17/72
Abstract:
An orthopaedic fixation assembly for prosthetic biologic attachment. The orthopaedic fixation assembly may include a main body with a longitudinally-extending stem having a proximal end, a distal end, and a cavity body. An anchor plug may be configured to be received within the stem cavity, and securable thereto via complementary mating surfaces. A spindle structure may be fixedly attached to the proximal end of the longitudinally-extending stem and protrude outwardly therefrom such that a portion of the structure extends externally beyond the resected cavity of the bone that may prevent rotational motion of the spindle. The spindle structure may have at least one compliant biasing member configured to apply a compressive force to the surrounding bone. A porous coating may be at the juncture between stem and spindle structure, on the spindle, and the splines and anti-rotation chocks, improving the initial stability of the implant and facilitating long-term bone ingrowth.

Method For The Analysis Of Progression Of Heterotopic Ossification By Raman Spectroscopy

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US Patent:
20160353994, Dec 8, 2016
Filed:
Jan 2, 2014
Appl. No.:
14/146334
Inventors:
Nicole Crane - Washington DC, US
Eric A. Elster - Kensington MD, US
Jonathan Forsberg - Kensington MD, US
Douglas Tadaki - Frederick MD, US
International Classification:
A61B 5/00
A61B 10/02
A61B 6/00
G01N 21/65
G01N 33/483
Abstract:
A method for detecting and monitoring the progression of heterotopic ossification by Raman spectral analysis. Analysis of heterotopic ossification progress can be conducted using invasive or invasive means using specific Raman spectroscopy. Analysis is by determination of a number of Raman spectral parameters including the area under one or more of the vibrational bands, band area ratios, band height, ratios of band heights and shift in band center.
Control profile
Jonathan A Forsberg from Berkeley, CA, age ~52 Get Report