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    Today, the DiaCeph device is characterized as an "artificial intelligence" (AI) application. Simplified versions of AI technology are currently being used in disease management to monitor asthma, congestive heart failure (CHF), and diabetes. Such applications could be implemented through modification of the DiaCeph technology.

    The patented DiaCeph technology and variations of it can be made to monitor other applications, such as outcomes assessment and clinical trials evaluations of new drugs, post market health risks monitoring for problem drugs such as Vioxx, non-invasive monitoring for early onset of stroke and other neurological disorders, and for new AI assistive technologies to enhance cognitive performance in individuals at many levels, and in many occupations.

    The Lawrence Berkeley National Laboratory, a cooperative effort between the U.S. Department of Energy and the University of California at Berkeley, is listed as a possible other use of technology - as they have numerous AI based projects with an emphasis in energy. Click here Lawrence Berkeley National Laboratory to go to their site. Music & Art Therapy is another possible AI application. Lastly, this web site's research study on Neuro-Compensatory Therapy by Stephen Dolle revealed new findings in these therapies that target hippocampus, memory, and vestibular deficits, including those suffering Post Traumatic Stress Disorder.

    While Stephen Dolle was in California designing his DiaCeph Test, researchers at the University of Pittsburgh, with funding from the Pittsburgh Steelers' football team, were busy pioneering a similar AI program for concussion, the IMPACT Test. This device helps physicians, trainers, and sports officials in better understanding subtle neurological changes often associated with concussion. Today, NASCAR employs it when evaluating race car drivers after a suspected concussion. This device enables an on site evaluation, and results can be similarly compared to baseline test data taken before the injury occurred. The resulting data is often more sensitive than CT or MRI imaging.