us.graph.md - brain

After the registration and interactivity process, the multi-agent system has the function of contextualizing Intelligence with suggestions and automation that people authorize. Here the challenge is the migration of contexts between the knowledge clouds and the cross-sectional analysis in the timelines. The theoretical problem within the universe of complex systems is that small variations in the parameters of the automaton processing cells generate profound changes in the final results. Therefore, the proposal is to work with epicritical and protopathic systems that are already well-defined in the area of neuroscience. Another difference is the explicitly non-existent relationships since the brain works with a constant fluctuation between the next step and the final destination. And therefore, it knows which paths it wants to avoid. Therefore, the creation of explicit relationships and nodes that do not exist is of fundamental importance. It is observed that in the current paradigm, there are very few solutions developed with explicitly recorded records of relational data that are not from a specific client or patient. Perhaps due to a lack of concern for more complex analyses, or even for issues of basic human cognition, if information is not related to this client, it simply should not be registered.

But, for example, in the universe of knowledge management in the healthcare area, knowing that a person does not have COVID-19 is not limited to the fact that this information is not registered in their records. Information from test records is necessary, and now, regardless of the result, positive or negative, this must be explicitly stated in the test performed. With just one simple example, but important, as it defines the life or death of a person in these post-pandemic times, we have the fair idea that we must work with inversely complementary bases. What are all the complementary nodes and relationships that this person has, or does not have, about the reference group? This concept should also be applied to direct interactions with users, allowing inverted filters to explicitly exclude nodes and relationships to clean up the visualization perspectives. Even high-volume applications such as Google do not provide explicit support for suppressing results, as it is practically impossible to find the name of a researcher who shares the same name as a celebrity on this technology giant's search engine.

The most complex computational concepts of the proposed model require a graph, but not just one! This is the basis for building a customized model to enable the development of highly sophisticated usability required of intelligent systems that will be part of the next generation of technological super applications in the knowledge era.

The illustrative diagram shows the map related to the neuroscientific concepts of executive control of the brain used as a reference in the knowledge synthesis project.

10-year follow-up o
epilepsy surgery patients

The map shows neurological care with a 10-year follow-up of patients who underwent epilepsy surgery.

An important issue in order to provide the physician with the necessary information at all times is the pre-filling of electronic forms that request the insertion of new information, based on previous responses. Using as a basis the diagnostic maps themselves that were later applied to these patients. The objective of filling in information oriented to patient information is to supply the maps with the necessary information during the interaction in the diagnostic process. If the physician thinks of a new hypothesis, not initially predefined in the maps, a new electronic form is then generated to be filled out that would allow the physician to ratify or exclude the new diagnostic hypothesis. These chosen paths are similar to the response of an artificial neural network, with the difference that not only the answer is provided, but also the path taken, which is as important as the answer within the diagnostic process, since, when questioned about each diagnostic hypothesis, the physician justifies, through an explainable AI, this answer with the reasons that led to each choice. The proposal implements a level of abstraction higher than the operation established by artificial neural networks. The nodes are concepts and represent the sum of the connections proposed by the artificial neural network. This new model is not linked to constant learning, and all learning depends on the expert's certification in a self-constructive map of possibilities.

E1: “I would like the entire book to represent just one idea.” Comment from the author to a friend! Gustave Flaubert talks about his masterpiece Madame Bovary. This highlights the real gap that needs to be filled! Very well-defined models that cannot diagnose the patient in consultation! But if we could identify all patients who are approximately the same as him! From there, build a synthetic conceptual model to identify the complementary concepts that would lead us to the diagnosis! With 30 concepts we could choose symptoms/classifying tests, going through a base of 30 thousand concepts that would lead us to a diagnostic target!

E2: So, the idea is to use a new way of constructing knowledge based on the ideas of Nonaka (the pope of Knowledge Engineering) and Nishida (Ba and Basho Concepts).

E3: (Definition of the Concept of Ba by Nishida) Ba: PLACE OF KNOWLEDGE CREATION. To include the concepts of these places, but to be specific to the creation of knowledge, we introduce the concept of “Ba” (roughly meaning “place”). Drawing from the concept originally proposed by the Japanese philosopher Kitaro Nishida (1921, 1970), we define “Ba” as a shared context in motion in which knowledge is shared, created, and utilized. “Ba” provides the energy, quality, and locations to effect individual conversions of knowledge and advance the spiral.

E4: Defining Basho’s Concept: In his 1926 essay “Basho,” he examines the idea (which can be translated as “place” or “locus”) and establishes Basho as its original logic. It is Basho’s logic that lays the foundation for Nishida’s philosophy, as it opens up from a theory of knowledge to encompass the aspect of the “historical world.” As the above outline shows, Basho’s concept is an intersection of Eastern and Western thought, and the Zen approach to reality underlies Basho’s logic. Nishida compares the characteristics of Eastern culture, in particular, Japanese culture: “seeing form without form.” What is the meaning of the contradictory expression “seeing form without form?” How does Nishida integrate this Japanese concept into Basho’s logic? We will examine these questions focusing on their Japanese aspects. Nishida was the first modern thinker to work towards establishing the relationship between Western (I think, therefore I am) and Eastern (I feel, therefore I am) philosophies. In this sense, then, two basic elements of his work are form without form; and the perception of time. E5: Form without form: The language part of your brain is reduced to 1 part among 40 others. It is in this region that Broca’s area is located. The special region of the prefrontal cortex contains a circuit necessary for the formation of words. Note the fact that 39 other parts of the brain have other functions. Now, how can we think that the entire functioning of our brain is reduced to what we think in words and concepts? In this sense, and thinking from a computational point of view, there is a limit to formalized thought represented by the expression: “form”. But there is thought that is not defined in words. Hence the idea of thought without words, or as our philosopher defines it: “Form without form”. The importance of this concept is related to the level of abstraction. The boundary between machines and human beings. We cannot formalize anything beyond what human beings form in their thoughts. Thus, computational efforts focus on formalizing the minimum number of concepts with the maximum possible impact, always seeking to contextualize what is the gap in human reasoning from the point of view defined by Daniel Kahneman in the book: Thinking, Fast and Slow.

E6: It is not you who is inside time, it is time that is inside you: imagine yourself parachuting out of an airplane. Now describe, or imagine, each moment until the parachute opens. Now describe a day at work or in the classroom. In the example of skydiving, time is within you, because your perception can describe each moment in an impressively rich way, full of senses and emotions. On the other hand, when we turn on autopilot, then yes, it is you who is within time.

E7: Thank God class or work is over. So, if in this series, at some point you gained knowledge! If for a moment you liked what you read and were able to relate a concept to be applied positively in your life. At that moment, time was within you.

E8: In this way, based on these initiatives, we could contribute to the proposal for creating a knowledge synthesis methodology to try to reduce this gap between AI and Conceptual Modeling! For example, in the universe of Neurology knowledge: a top ontology of all patients in the world. A base ontology of just one patient in neurological care in the world. A synthesis of the knowledge of all patients approximately equal to that specific patient.

E9: The identification and reconstruction of an ontology-based only on this specific group would allow us to identify the complementary concepts of the patient under analysis about the other patients in the group already analyzed (diagnosed). We sincerely believe that technologically we are at a time when everything is ready to build synthetic knowledge. All you need to do is change the point of view of development. Think about people instead of companies.

E10: This initiative to build personal knowledge bases is a possible path for new generations of knowledge engineers who will create knowledge interactively and continuously from intelligent systems. Without even knowing the border between knowledge engineering and AI.

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10-year follow-up o epilepsy surgery patients

The map shows neurological care with a 10-year follow-up of patients who underwent epilepsy surgery.

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10-year follow-up o
epilepsy surgery patients