Making Medicine a Science
One of the fundamental tasks of a scientist is to prove our work. To do this we must be able to measure what we are looking for or trying to observe.
These measurements then allow us to make comparisons to determine if what we think we are observing is real and if what we have done in our research experiments has produced a real change.
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To make these comparisons we need actual measurements and a method to compare those measurements - i.e. we need statistics. Statistics is the math we use to keep from fooling ourselves into believing something is real, when it isn't and vice-versa.
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Not everything can be seen with the naked eye or even with a microscope. Electron microscopes can see still smaller items; but, the process kills anything living.
Sometimes the change you are looking for is so small it must be measured by instruments capable of seeing and measuring, what you cannot.
In this instance, the scientist relies heavily on the accuracy of the instrument or equipment being used - accuracy that only exists if the equipment is calibrated with a known standard.
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For physicists like myself, this is not uncharted territory.
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The work I have done during my lifetime has included working with particles and energy far too small to be seen; but, they and their effect can be measured.
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Many diagnostic tests in medicine take advantage of images produced by these energies which are too small to be seen.
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These energies are detected by medical imaging equipment which use computers to produce images. Images which are then depended upon to make decisions about the presence or absence of a health problem. Decisions about treatment and decisions about life and death.
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As you will soon see, research I have carried out during the last 2-3 decades has demonstrated that the medical imaging devices - while providing pretty pictures - are fundamentally flawed.
These flaws exist in FIVE primary categories:
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1) Failure to standardize the equipment to produce accurate, reproducible results - from which images are provided,
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2) Failure to understand the nuclear isotopes being used,
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3) Failure to understand and apply correct timing of image acquisition to avoid missing a problem when present,
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4) Failure to recognize important biological differences critical to understanding the health (disease) spectrum - i.e. regional blood flow and metabolic differences, and
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5) Failure to understand that the spectrum of health (disease) follows the response of the body to an InflammoThrombotic Immunologic Response (ITIR) which ultimately is expressed as a Disease (ITIRD), which can be measured by measuring regional blood flow and metabolic differences.
The following video was recorded by me in 2017 after receiving my FMTVDM patent, which quantitative measures regional blood flow and metabolic differences inside the body.
Coupled with the 1994 ITIRD theory first presented by me at the American Heart Association (AHA) Conference in Dallas, TX, FMTVDM corrects and addresses these FIVE fundamental flaws.
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