JONATHAN A FORSBERG
Physician at Everett St, Kensington, MD
License number
Florida 8534
Issued Date
Jan 3, 2005
Effective Date
Aug 16, 2011
Expiration Date
Jan 3, 2007
Category
Health Care
Type
Registration for Resident/HSE Physician
Address
Address
2
3814 Everett St, Kensington, MD 20895
807 Children's Way CHILDREN'S WAY, Jacksonville, FL 32207
807 Children's Way CHILDREN'S WAY, Jacksonville, FL 32207
Professional information
Clinical Decision Model
US Patent:
2011028, 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
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
US Patent:
2011028, 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
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
US Patent:
2011029, 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
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.