Summary of an idea
Observing mammoth expenses in medical treatment I have been planning to develop a cognitive cloud medical app to detect the disease accurately and generate its proper treatment procedure through generic medicination if the gene history of individual can find out from the human body radiation, analysing through AI and instant output as to render the prompt service in few touch on mobile app. So, it can be the revolutionary measure in medical treatment history bypassing unnecessary major expenses incurred by patients and their families which is not affordable.
Initially if I can develop such app yet, it will try to distribute the app among the people at no cost subject to relation of developing the big project if magnitude of cost arise havoc, then it can be charge to access the app $10, the common people can afford.
Two things I have to bear in brain that the app can access offline and the result should be 100% accurate; no scope or error should come in the argument during the programming and selection of program language/s.
How the disease could be detected?
The idea first came in my mind from an essay was written by LEE Shank-ming, Olivia September 2010.
Has it ever occurred to your body is emitting radiation? Yes, all objects, including human bodies, emit electromagnetic radiation. The wavelength of radiation emitted depends on the temperature of the objects. Such radiation is sometimes called thermal radiation. Most of the radiation emitted by human body is in the infrared region, mainly at the wavelength of 12 micron. The wavelength of infrared radiation is between 0.75 to 1000 micron (1 micron = 10 to the power minus 6 metres). This wavelength is longer than that of red visible light so this explains the name ‘infrared’, meaning ‘beyond the red’.
Note : Normal body temperature is recorded of a healthy human is 98.5% farenhite. If any disease occurs naturally the normal body temperature will go change, either up or down, naturally emission of radiation will differ. If the data base can create comprehensively according to categorically that which disease denote the what wave length in infrared so it can easy to detect the disease primarily.
IR image
IR image or Infrared image, the characteristics of the IR radiation emitted by the human body were investigated by measuring the dependence of the facial surface temperature on the atmosphere temperature and solar radiation. The results made it clear that the facial surface temperature shows little change under a condition of a light wind.
The maximum radiation intensity wavelength λm can be found with Wien’s displacement law as λm x T=2.897 ±0.4 µmxK
In future research work, it will be necessary to enhance the sensivity of the IR imaging sensor so that it functions more effectively under various environmental conditions and to improve the weatherability of the optical system.
Near-infrared spectroscopy (NIRS)
This is a spectroscopic method that uses the near-infrared region of the electromagnetic spectrum. Typical applications include medical and physiological diagnostics and research including blood sugar, pulse oximetry, functional neuroimaging, sports medicine, elite sports training, ergonomics, rehabilitation, neonatal research, brain computer interface, urology (bladder contraction), and neurology (neurovascular coupling).
Brain-computer interface
A system that uses brain activity to switch on genes with light could give new meaning if in relation to string with human infrared wave length in normal and in abnormal condition, argumentive with data mining in various stages in various diseases; and if the input place properly, cognitive to scaling the brain-computer interface adding sofisticated nano chip in operation, then the revolutionary app or cognitive cloud computing can compute can detect any disease accurately along with its proper treatment procedure within few minutes with proper generic medicination.
Conclusion of the tiny idea
This is the rough sketch of my idea. But doing it into material I do need support of various medical data of various places of the different patients, so can easily categorise the normality and abnormality differentiate with proper reasons.
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