Logic of medical language 3

Encryption

Let us continue with our example:

Let us take a common encryption and decryption platform. In the following example we will report the results of an Italian platform but we can choose any platform because the results conceptually do not change:

You type your message in plain text, the machine converts it into something unreadable, but anyone knowing the "code" will be able to understand it.

Let us suppose, then, that the same happens when the brain sends a message in its own machine language, made up of wave trains, packets of ionic fields and so on; and that carries a message with it to decrypt the ‘Ephaptic’ code.

This message from the Central Nervous System must first be transduced into verbal language, to allow the patient to give meaning to the linguistic expression and the doctor to interpret the verbal message. In this way, however, the machine message is polluted by the linguistic expression: both by the patient, who is unable to convert the encrypted message with the exact meaning (epistemic vagueness), and by the doctor, because he/she is conditioned by the specific context of his/her specialization.

The patient, actually, by reporting a symptomatology of orofacial pain in the region of the temporoandibular joint, virtually combines the set of extension and intention into a diagnostic concept that allows the dentist to formulate the diagnosis of orofacial pain from temporomandibular disorders. (TMDs).

Very often the message remains encrypted at least until the system is damaged to such an extent that clinical signs and symptoms emerge so striking that, obviously, they facilitate the diagnosis.

Understanding how the encryption works is quite simple (go to decryption platform chooses and to try it out):

1. choose an encryption key among those selected;
2. type a word;
3. get a code corresponding to the chosen key and the typed word.

For example, if we insert the word ‘Ephaptic’ in the platform encryption system, we will have an encrypted code in the three different contexts (patient, dentist and neurologist) which correspond to the three different algorithmic keys indicated by the program, for instance: the A key corresponds to the patient's algorithm, the B key to the dental context and the C key to the neurological context.

In the case of the patient, for example, writing Ephaptic and using the A key, the "machine" will give us back a code like

$133755457655037A$

The key can be defined as "Real context".

«Why do you say that the patient's "key" is defined as the REAL one?»
(difficult answer, but please observe the Gate Control phenomenon and you will understand)

First of all: Only the patient is unconsciously aware of the disease that afflicts his own system, but he does not have the ability to transduce the signal from the machine language to the verbal language. The same procedure occurs in 'Systems Control Theory', in which a dynamic control procedure called ‘State Observer’ is designed to estimate the state of the system from output measurements. Matter of fact, in the control theory, observability is a measure of how much the internal state of a system can be deduced from the knowledge of its external outputs. While in the case of a biological system a ‘Stochastic Observability’ of linear dynamic systemsis preferred, the Gramian matrices are used for the stochastic observability of nonlinear systems.

This would already be enough to bring now our attention on an extraordinarily explanatory phenomenon called Gate Control. If a child gets hit in the leg while playing soccer, in addition to crying, the first thing he does is to rub extensively the painful area so that the pain decreases. The child does not know the ‘Gate Control’, but unconsciously activates an action that, by stimulating the tactile receptors, closes the gate at the entrance of the nociceptive input of the C fibres, consequently decreasing the pain; the phenomenon was discovered only in 1965 by Ronald Melzack and Patrick Wall.

As much as in computers, encryption-decryption also takes place in biology. In fact, in a recent research the authors examined the influence of molecular mechanisms of the ‘long-term potentiation’ (LTP) phenomenon in the hippocampus on the functional importance of synaptic plasticity for storage of information and the development of neuronal connectivity. It is not yet clear if the activity modifies the strength of the single synapses in a digital (01, all or nothing) or analog (graduated) way. In the study it emerges that individual synapses appear to have an 'all or nothing' enhancement, indicative of highly cooperative processes, but different thresholds for undergoing enhancement. These findings raise the possibility that some forms of synaptic memory may be digitally stored in the brain.

Decryption

Now, assuming that the machine language and the assembler code are well structured, we insert the encrypted message from the Mary Poppins System in the 'Mouth of Truth‘:

$133755457655037A$

Let's pretend that we are Martians in possession of the right key (algorithm or context) the A key that corresponds to the 'Real Context'. We would be able to perfectly decrypt the message, as you can verify by entering the code in the appropriate window:

«Ephaptic»

But, luckily or not, we are not Martians, so we will use, contextually to the information acquired from the social and scientific context, the dental key that correspond to B key, with the consequent decryption of the message into:

«5GoI49E5!»

Using the C key that corresponds to the neurological context, the decryption of the message would be:

«26k81n_g+»

These are extraordinarily interesting elements of language logic, and please note that the encrypted message of the real context ‘meaning’ of the ‘disease’, the A key, is totally different from the one encrypted through the B keys and the C key: they are constructed in conventionally different contexts, while there is only one reality and this indicates a hypothetical diagnostic error.

This means that medical language logics mainly built on an extension of verbal language, are not very efficient in being quick and detailed in diagnostics, especially the differential one. This is because the distortion due to the ambiguity and semantic vagueness of the linguistic expression, called ‘vagueness epistemic’ or ‘epistemic uncertainty’, or better ‘uncertain knowledge’, forcibly directs the diagnosis towards the specialist reference context and not on the exact and real one.

«Why, then, are we relatively successful in diagnostics?»
(An entire separate encyclopedia would be needed to answer to this question, but without going too far, let's try to discuss the reasons.)

Basic diagnostic intuition is a quick, non-analytical and unconscious way of reasoning. A small body of evidence indicates the ubiquity of intuition and its usefulness in generating diagnostic hypotheses and ascertaining the severity of the disease. Little is known about how experienced doctors understand this phenomenon, and about how they work with it in clinical practice. Most reports of the physician’s diagnostic intuition have linked this phenomenon to non-analytical reasoning and have emphasized the importance of experience in developing a reliable sense of intuition that can be used to effectively engage analytical reasoning in order to evaluate the clinical evidence. In a recent study, the authors conclude that clinicians perceive clinical intuition as useful for correcting and advancing diagnoses of both common and rare conditions

It should also be noted that the Biological System sends a uniquely integrated encrypted message to the outside, in the sense that each piece of code will have a precise meaning when individually taken, while if combined with all the others it will generate the complete code corresponding to the real message, that is to "Efapsi".

In short, an instrumental report (or a series of instrumental reports) is not enough to decrypt the machine message in an exact way corresponding to reality. If we expect the message to be decrypted from 2/3 of the code, which perhaps corresponds to a series of laboratory investigations, we would get the following decryption result:

«Ef+£2»

This outcome comes from the deletion of the last two elements of the originating code: $13375545765503$ resulting from $133755457655037A$. So, part of the code is decrypted (Ef) while the rest remains encrypted and the conclusion speaks for itself: it is not enough to identify a series of specific tests, yet it is necessary to know how to tie them together in a specific way in order to complete the real concept and build the diagnosis.

Therefore, there is a need for:

«A System Logic that integrates the sequence of the machine language code»
(true! we'll get there with a little patience)

Final Considerations

The logic of language is by no means a topic for philosophers and pedagogues; but it substantially concerns a fundamental aspect of medicine that is Diagnosis. Note that the International Classification of Diseases, 9th Revision (ICD-9), has 6,969 disease codes, while there are 12,420 in ICD-10 (OMS 2013). Based on the results of large series of autopsies, Leape, Berwick and Bates (2002a) estimated that diagnostic errors caused 40,000 to 80,000 deaths annually. Additionally, in a recent survey of over 6,000 doctors, 96% believed that diagnostic errors were preventable.

Charles Sanders Peirce (1839–1914) was a logician and practicing scientist; he gradually developed a triadic account of the logic of inquiry. He also distinguishes between three forms of argumentation, types of inference and research methods that are involved in scientific inquiry, namely:

1. Abduction or the generation of hypotheses
2. Deduction or drawing of consequences from hypotheses; and
3. Induction or hypothesis testing.

In the final part of the study conducted by Donald E Stanley and Daniel G Campos, the Peircean logic is considered as an aid to guaranteeing the effectiveness of the diagnostic passage from populations to individuals. A diagnosis focuses on the individual signs and symptoms of a disease. This manifestation cannot be extrapolated from the general population, except for a very broad experiential sense, and it is this sense of experience that provides clinical insight, strengthens the instinct to interpret perceptions, and grounds the competence that allows us to act. We acquire basic knowledge and validate experience in order to transfer our observations into the diagnosis.

In another recent study, author Pat Croskerry proposes the so-called "Adaptive Expertise in Medical Decision Making", in which a more effective clinical decision could be achieved through adaptive reasoning, leading to advanced levels of competence and mastery.

Adaptive competencies can be obtained by emphasizing the additional features of the reasoning process:

1. Be aware of the inhibitors and facilitators of rationality (Specialists are unwittingly projected towards their own scientific and clinical context).
2. Pursue the standards of critical thinking. (In the specialist, self-referentiality is supported and criticisms from other scientific disciplines or from other medical specialists are hardly accepted).
3. Develop a global awareness of cognitive and affective biases and learn how to mitigate them. Use argument that reinforces point 1.
4. Develop a similar depth and understanding of logic and its errors by involving metacognitive processes such as reflection and awareness. Topic is already mentioned in the first chapter ‘Introduction’.

In this context, extraordinarily interesting factors emerge that lead us to a synthesis of all what has been presented in this chapter. It is true that the arguments of abduction, deduction and induction streamline the diagnostic process but we still speak of arguments based on a clinical semeiotics, that is on the symptom and/or clinical sign. Even the adaptive experience mentioned by Pat Croskerry is refined and implemented on the diagnosis and on the errors generated by a clinical semeiotics.

Therefore, it is necessary to specify that semeiotics and/or the specific value of clinical analysis are not being criticized because these procedures have been extraordinarily innovative in the diagnostics of all time. In the age in which we live, however, it will be due to the change in human life expectancy or the social acceleration that we are experiencing, ‘time’ has become a conditioning factor, not intended as the passing of minutes but essentially as bearer of information.

In this sense, the type of medical language described above, based on the symptom and on the clinical sign, is unable to anticipate the disease, not because there is no know-how, technology, innovation, etc., but because the right value is not given to the information carried over time

This is not the responsibility of the health worker, nor of the Health Service and nor of the political-industrial class because each of these actors does what it can do with the resources and preparation of the socio-epochal context in which it lives.

The problem, on the other hand, lies in the mindset of mankind that prefers a deterministic reality to a stochastic one. We will discuss these topics in detail.

In the following chapters, all dealing with logic, we will try to shift the attention from the symptom and clinical sign to the encrypted machine language: for the latter, the arguments of the Donald E Stanley-Daniel G Campos duo and Pat Croskerry are welcome, but are to be translated into topic ‘time’ (anticipation of the symptom) and into the message (assembler and non-verbal machine language). Obviously, this does not preclude the validity of the clinical history (semeiotics), essentially built on a verbal language rooted in medical reality.

We are aware that our Linux Sapiens is perplexed and wondering:

«... could the logic of Classical language help us to solve the poor Mary Poppins' dilemma?»
(You will see that much of medical thinking is based on the logic of Classical language but there are limits)

Bibliography

Bibliography & references

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particularly focusing on the field of the neurophysiology of the masticatory system
 

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