David M Halverson

US Patent:

20110134937, Jun 9, 2011

Filed:

Jul 17, 2009

Appl. No.:

12/675023

Inventors:

Ted Lichoulas - Simpsonsville SC, US
Eddie Kimbrell - Dacula GA, US
David Halverson - Moore SC, US

Assignee:

AFL TELECOMMUNICATIONS ,LLC. - Spartanburg SC

International Classification:

H04L 12/66

US Classification:

370463

Abstract:

Provided is a network module, the module including a base unit, wherein the base unit includes at least one mating element that couples to a corresponding mating element of a network interface device; at least one connector element that couples to an add-on module; and the add-on module, wherein the add-on module includes at least one mating element corresponding to the connector element of the base unit, wherein the base unit is configured to interface with the add-on module and wherein the base unit is electrically connected to the add-on module.

US Patent:

20190355478, Nov 21, 2019

Filed:

Dec 29, 2017

Appl. No.:

16/475349

Inventors:

- McLean VA, US
Michael Jon PISHVAIAN - Potomac MD, US
Robert Joseph BENDER - Rockville MD, US
Edik Matthew BLAIS - Charlottesville VA, US
Craig HEARTWELL - Herndon VA, US
Samuel Brewster LESLIE - Burke VA, US
David Charles HALVERSON - North Bethesda MD, US
Jonathan Robert BRODY - Philadelphia PA, US

Assignee:

PERTHERA, INC. - McLean VA

International Classification:

G16H 50/70
A61B 5/00
A61N 5/10

Abstract:

A method and system for generating a therapy plan for a patient is described. The method includes providing a knowledgebase of annotated disease treatment information, a patient history database including disease types for a plurality of patients and a molecular database including molecular data associated with patients, selecting at least one of the plurality of patients for analysis, identifying a list of one or more candidate therapy plans from the knowledgebase based on at least one of the disease type and the molecular data for the at least one patient, and scoring each of the one or more candidate therapy plans by combining a molecular vector, a disease-specific vector and a patient history vector. The therapy plan with the highest score can then be selected for implementation. The system includes various hardware components for implementing the various functions as defined by the method for generating the treatment plan.