To start off this lesson, we're going to review important ideas from fields such as cognitive science, linguistics, and computer science that creates ways to organize our knowledge about the world. We need to understand how people conceptualize their lives and problems and communicate complex ideas. This is important for all aspects of life, but it's especially relevant to health and medicine, where there are huge number of abstract and complicated concepts. After this lesson, you will be able to compare literal versus metaphorical forms of communication and describe why both philosophers and medical informaticists use ontologies to describe the world. Let's get going into a quick introduction of Greek philosophy. Now, before we move into the discussion of human categorization and creation of communication of knowledge, we should review some terms that you might see in an introductory philosophy course. First, metaphysics is a branch of philosophy that has to do with the nature of being, reality, and existence. No small subject for sure. Ontology is a term for what there is within the world. Epistemology has to do with what humans can know about the world. The Greeks thought that people could directly access the essences of our worlds. Thus, for them, there was not a conflict between ontology, what there is in the world, and epistemology, where we can actually know about the world. Later, philosophers, such as Rene Descartes, thought about the gaps between what is out there in the world and what can be known. Lakoff and Johnson explain that the body was the flesh of the world and the mind was not. Thus, ideas in the minds are separate from objects in our world. Much of modern philosophy seeks to find correspondences between our representations of world objects and the reality out there. I have recently become a convert to Lakoff and Johnson's idea that is closer to the original Greek approach. They believe in an embodied realism approach in which the human conceptual system and ability to categorize and explain the world starts with more simple experiences we have within our bodies and interactions with other people. As a result, we use metaphors to understand our complex world, and these impact all domains of our perception. Okay. Now that you have that, let's take a brief tour into the field of cognitive linguistics to illustrate that much of human communication and speech is actually non-literal or figurative. Thus, although we sometimes assume that most of our conversations evolve concrete and non-abstract terms, it is more likely that nearly all abstract concepts need to be understood using sets of simpler concrete terms. It is interesting to me that there's a growing evidence that metaphorical language is used to help humans with more complex ideas. Let's take the complex idea of love. George Lakoff and Mark Johnson show us that many of our human emotions are described using orientational metaphors. Thus, happy is up, sad is down. You might hear people in the United States say that they're feeling up today or that the party boosted their spirits. Sadness, alternatively, is expressed as being down, as in the bad news brought him to a new low. Complex topics, such as how people describe their lives, is often metaphorical. In the United States, many people see their lives as journey. People talk about going down the road or a path or crossing bridges to get to their destination. Similarly, people think about love as a journey. When times are good, relationship is moving down the road. When the relationship fails, a couple might metaphorically talk about being at the crossroads of parting ways, or that the relationship is heading towards the rocks, is when a ship crashes on the shore. Sometimes love is magic. For example, she hypnotized me and cast a spell on me. Sometimes love is war. For example, we fought, but in the end, she worn out. Thus, a key idea is that most of the forms of human communication is non-literal. Contexts of the discussion is often required to interpret the meaning of what others are saying. Similarly, data are not inherently meaningful unless a person understands the context of how the data were created, for what purpose, how stored, and how transformed and were various ways to help people make decisions. As I just mentioned, ontology seek to describe what there is out there within our human and nonhuman worlds. Thus, ontologies are highly descriptive. They seem to completely define concepts and relationships within a given domain. Additionally, they help us come with a defined set of rules or set of characteristics about concepts that further help us define what a concept is and is not. For this reason, ontologies are used mainly as a referential dataset for classification and data exploration tasks. An example of a classification task that can be performed with an ontology could look something like this. Let's say we want to understand how often our doctors are prescribing aspirin or aspirin analogues for the use in their patient population. Thousands of drugs meet the criteria of being either aspirin or an aspirin analog. In this case, we'd use the ontology to compare every medication order to see if it fits within the rules that are built around describing what an aspirin or an aspirin analog is, thus allowing us to classify each one of our very different medication orders into logical groupings of aspirin or aspirin analogues. With our definition of ontologies or descriptions of our human world, let us now shift to a data exploration perspective. An analyst may wish to look at a patient's medical record and see how many aspirin analogues related to drugs they are on. It is possible to use the intricately define relationships within an ontology to understand how many other drugs the patient is already on that may have similar pharmaceutical effects as aspirin, thus empowering the physician to do a better job at assessing whether aspirin is truly indicated. Because of their descriptive power, the use of ontologies can be computationally intensive, especially as they grow large. It's unlikely you'll regular use an ontology in practice. However, the term ontology is often intertwine with medical terminologies. So, you will hear the word thrown around in day-to-day practice. Likely, the first ontology that will be widely adopted in medicine will be SNOMED CT, but that is years away from widespread acceptance. If you're interested in reading more about ontologies, please look up the Stanford Protege Project or SNOMED CT itself. We'll go into this more later in the next lesson, but I want to bring up the concept of terminology versus an ontology. A terminology is a list of words, terms, and their definitions. Thus, it is a kind of dictionary. An ontology is a list of terms and set of rules that go along with that list of terms that enforced the semantic integrity of the coded values. This is a set of rules that will allow you to be assured that you're always going to be representing what you intend to be representing. It's important for us to understand the difference in it if we're not going to be building our own terminologies or ontologies. In the next lesson, we'll talk about standard terminologies in health care. See you then.
