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Biosemiomics, the New Research Technique from the Cause-Effect Perspective

Víctor Alfonso Abuadili Garza

2025International Science Journal6 citationsDOIOpen Access PDF

Abstract

We have focused on paying attention to disease, knowing how to diagnose it, how to treat it, how to "eliminate" or control it. But I assure you that very few people in this world have become aware and consistent, and instead of thinking about eliminating the disease, they think about preventing it from developing. After years of research, this author has concluded that, according to the International Code of Diseases (ICD-11), there are more than 44,000 reported diseases, and more are described each year; however, there are only ten causes for all diseases. Biosemiomics is a new scientific concept that corresponds to the study of causal processes, signs and symptoms that a person may present before the development of the disease, the management of the living systems involved, which includes both a theoretical description of the processes that living nature can affect the development of these conditions, and especially the metabolic processes that occur within the human body; with a vision of life itself, that is, of the natural history of all the acts and events that occur before the clinical diagnosis, according to the allopathic definition. The objective of this study is to interrelate, through biosemiotics, the bridge that exists between biology, semiotics, and Applied Omics Sciences, using Metabolic Assessment under the System for the Application of Techniques for Metabolic Diagnosis (ATDM System). Results: The six components of biosemiomic study have been identified, defining their content and scope. Conclusions: Through this study, we have established the components of Applied Clinical Biosemiomic Research using the ATDM System methodology, and we can now explore their interrelation with different diseases.

Topics & Concepts

Perspective (graphical)Control (management)Natural (archaeology)EpistemologyPsychologyComputer scienceBridge (graph theory)Affect (linguistics)Management scienceRisk analysis (engineering)Process (computing)Engineering ethicsData scienceCausality (physics)Identification (biology)CausationMechanism (biology)SociologyMeaning (existential)Component (thermodynamics)Clinical PracticeUnexpected eventsCancer and biochemical researchScientific Research and TechnologyNutrition, Genetics, and Disease
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