Mobile Application for Healthcare, Epidemiology, & Safety (MAES)

The MAES initiative designed and developed technology that collects data from multiple sources, analyzes the data for trends and patterns, and, using handheld devices, deliver context sensitive, location based alerts and advice to users on healthcare, disease, safety, and environmental related issues.

Humanitarian relief, disaster recovery, nation building:  these missions are becoming more significant for both military and non-governmental organizations every day.  Health awareness and a proactive approach to health outcomes are critical to these missions, but, in many developing countries, even basic reporting of the health status of affected populations can be a daunting task.  Communications infrastructures are minimal, transportation may be difficult, time is short, and the focus is often on addressing basic human survival needs.  Establishing baselines for epidemiological awareness may be too time consuming and difficult to be a priority.

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Medical Materiel Knowledge Discoverer (MMKD)

MMKD is a configurable, dashboard driven knowledge discovery system that allows users without data mining expertise to perform cutting edge knowledge discovery.  The technology helps the DoD Medical Logistics community meet the challenges of troop deployments in ever widening combat scenarios.

The Medical Materiel Knowledge Discoverer (MMKD) is a knowledge discovery system for the Department of Defense (DoD) Medical Logistics community that goes beyond simple data mining.  The changing nature of military conflicts in the world favor an emphasis on the rapid deployment of troops in an ever-widening variety of scenarios and locales.  These developments raise significant logistical challenges and risks for, among other military branches, the DoD medical community.

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Biosurveillance-based Integrated Outbreak Warning And Recognition System (BIOWARS)

The BIOWARS technology is an adaptive system for discovering disease outbreaks and impending bio terrorism attacks.  BIOWARS uses syndromic surveillance to find symptomatic data patterns and applies Bayesian networks in collecting and archiving these patterns.

An important challenge faced by intelligence analysts and the intelligence community in our post 9/11 world is to gather, piece together, and correctly interpret vast amounts of intelligence data–data that may signal an impending attack or that may help limit the severity of an attack.  As a Defense Science Board study of transnational threats noted, the “making of connections between otherwise meaningless bits of information is at the core of (transnational) threat analysis.”

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