Medical Materiel Knowledge Discoverer (MMKD)

Award Information
Agency: Department of Defense
Branch: Office of the Secretary of Defense
Contract: DAMD17-03-C-0063
Agency Tracking Number: O022-0520
Amount: $99,930.00
Phase: Phase I
Program: SBIR
Awards Year: 2002
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
1408 University Drive East, College Station, TX, 77840
DUNS: 555403328
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Satheesh Ramachandran
 Research Scientist II
 (979) 260-5274
 SRamachandran@kbsi.com
Business Contact
 Perakath Benjamin
Title: Vice President, Research
Phone: (979) 260-5274
Email: PBenjamin@kbsi.com
Research Institution
N/A
Abstract
"Improving responsiveness requires continual innovation, and technology has created the opportunity to use knowledge discovery for innovation and continual improvement in supply chain logistics. DMLSS can use knowledge discovery to increase medicallogistics support effectiveness while reducing costs in two distinct environments: Military Treatment Facilities (MTFs) and deployed theater forces. The changing composition of military activities, technology, and adversaries increases the possible rapiddeployment of forces in a widening variety of scenarios, with more potential medical risks and challenges. Therefore, DMLSS must be able to rapidly deploy knowledge discovery and apply results to supply chain logistics and the early detection of criticalevents. However, while many excellent data mining tools exist, the process of knowledge discovery and its application is elusive (and frustrating) for most organizations. The main goal of the proposed initiative is to design, develop, and validate aKnowledge Discovery Framework (KDF) for the DoD Medical Logistics community. The main product of this effort will be the Medical Materiel Knowledge Discoverer (MMKD), a configurable, dashboard driven system for knowledge discovery with drill downcapability for rapid navigation through data and rapidly deployable to capture knowledge, identify of out of balance conditions, and apply decision optimization techniques. The result of MMKD will be a solu

* Information listed above is at the time of submission. *

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