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19 March 2009 Biomedical wellness standoff screening by unsupervised learning
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Abstract
Biomedical Wellness (BMW) surveillance system may become indispensible in public health riding on four confluent trends: (i) The surge of retirement waves of WWII baby boomers; (ii) The longevity of the seniors, thanks to 3 decades steady NIH budgets~$23B per year; (iii) The economic melting down is exasperating resources for entitlements; (iv) The emergent Next Gen Internet having the last mile challenges solved entirely and friendly with IT wired and wireless delivery system, thanks to DoD/DARPA pioneer and numerous entrepreneurs visionary efforts. To be effective in job recreation in current economic slag, BMW needs a jump start, WH/HHS should establish a balanced investment policy in health care, not just to illness but to wellness, and a BMW blue ribbon panel (BMWbrp), which must be, however, independent of NIHbrp, recommending additional resources, say $5B budget for BMW infrastructure building that will surely create new jobs to prepare badly needed geriatric caretakers. Being governmental investment, the BMWbrp must come back with a upward-conversion compatible infrastructure Blue-Print, version#1, an open architecture of standard interfaces, workable with distributed data bases and programming languages. The infrastructure must be simple, transparent, scalable, to leverage with a win-win-win(senior) CRADA from the private investments worldwide, e.g. from the insurance companies and home security companies, etc. that can further attract senior community center BOT. To start whenever the rubber meets the road, we shall enlist the military infrastructure, their sensors suite located in DoD & DHS labs supported with their affiliated contractors and universities. However, the down selections should be done under open bids, oversight by BMWbrp, under HHS $5B budget, to translate their sophisticated military persistent and precision surveillance know-how technology to watch out, no longer the enemy of USA but also, the enemy of mankind, the malicious microorganisms and disorders. The degree of friendliness must be demanded and measured by the standoff methodology such as 4 nones: noninvasive, noncontact, and none-stop-to-measure, in this order.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Harold H. Szu, Charles Hsu, Philip Hoekstra, and Jerry Beeney "Biomedical wellness standoff screening by unsupervised learning", Proc. SPIE 7343, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII, 734319 (19 March 2009); https://doi.org/10.1117/12.821206
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