Military Health Data Mining Algorithms Library (M-HDML)

Award Information
Agency: Department of Defense
Branch: Office of the Secretary of Defense
Contract: DAMD17--02-C-0071
Agency Tracking Number: O2-0081
Amount: $729,800.00
Phase: Phase II
Program: SBIR
Awards Year: 2002
Solitcitation Year: N/A
Solitcitation Topic Code: N/A
Solitcitation Number: N/A
Small Business Information
Knowledge Based Systems, Inc.
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
 (979) 260-5274
 sramachandran@kbsi.com
Business Contact
 Perakath Benjamin
Title: Vice President
Phone: (979) 260-5274
Email: pbenjamin@kbsi.com
Research Institution
N/A
Abstract
"We propose to develop, build, and validate a Military Health Data Mining Algorithms Library (M-HDML), a set of reusable and extendible knowledge analysis software templates that facilitate the medical knowledge discovery process. Apart from delivering"data-driven" knowledge that is useful from a medical diagnostic/prognostic standpoint, the developed infrastructure would ultimately provide planners with information to measure various aspects of overall medical readiness. The successful Phase I project(i) developed a prototype M-HDML Toolkit and (ii) demonstrated its practical utility on actual MHS data sets and application scenarios. The Phase II project will (i) refine and harden the M-HDML architecture and software, (ii) develop two focused militarymedical applications, and (iii) generalize M-HDML for large-scale application and commercialization. The main products of the proposed effort will be (i) the HDML Toolkit and (ii) two focused M-HDML military medical software applications. The capabilityto mine the various health information systems would provide valuable medical knowledge that would ultimately augment the health services offered to the personnel and elevate the overall readiness of the armed forces."

* information listed above is at the time of submission.

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