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Thousands of medical, physiological, and health-related terms are listed alphabetically and Dictionary of Medical Terms (Barron's Medical Guides) 5th Edition.
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- Dictionary of Medical Terms - Barron's Educational Series - Literati by Credo
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Firstly, the years — were highly significant for the development of an English medical vocabulary, as it was in the late fourteenth century that English began to emerge from the shadow of Latin and French as the language of medical writing in England Voigts Many of the words used by the writers and translators did not, however, gain any wider currency and have not been recorded in any post texts. A second reason for examining medical vocabulary of the period — was its uneven coverage in existing historical dictionaries of English.
For practical reasons, MED and OED mostly analyse the vocabularies of printed works, including editions, and cannot devote similar attention to texts that only exist as manuscripts. The latter constitute a largely untapped resource for lexicological and lexicographic studies. The first printing-press in England was set up in , which means that most Middle English medical writings were handwritten manuscripts.
It has been observed that the compilers of the two dictionaries were somewhat inconsistent in their treatment of scientific and medical words, especially as concerns inclusion or exclusion of special vocabulary of Latin or French origin Norri ; McConchie ; Landau The target audience of DMV are lexicologists, lexicographers, editors of medical manuscripts, and historians of medicine. For anyone interested in studying Middle English and Early Modern English medical works, the terminology employed by contemporary writers presents a major challenge.
Many of the words and phrases have disappeared without a trace in the course of the centuries. For terms that are still used in modern medicine, the meaning is often different in the medieval text. The database underlying DMV is searchable and enables users to collect data on a variety of aspects relating to medical words and phrases in late medieval England. Examination of the general characteristics of medical vocabulary between and would be a painstaking effort using the circa page printed volume as the main source.
The corpus gathered for the dictionary comprises altogether 11, pages from late medieval manuscripts and printed books. In collecting the corpus, the printed manuscript catalogues of various libraries were first consulted. For locating medical books published during the period examined, the catalogue of early printed books by Pollard and Redgrave — was the main source. Treatises that proved to be short, or of a fragmentary nature, were not included, but both acephalous and atelous texts were admitted in those cases where an important medical work only survived in a unique incomplete version.
Medical writings in which languages other than English dominated were excluded from the corpus. One of the guiding principles in choosing the texts to be examined was inclusion of different types of medical treatises written in medieval England. Voigts introduced a now widely followed classification of Middle English medical writings based on the origin of the text and the tradition behind it. Voigts makes a distinction between remedybooks and academic medical texts.
Remedybooks form the older and larger group. They consist mainly of medicinal recipes, whose contents can be divided into six components: the purpose e. In addition to recipes, many remedybooks contain other kinds of material relating to the cure of illnesses and the maintenance of health. The reader may come across passages relating to for example blood-letting, diet, and the magical properties of plants and objects. The origins of particular remedybooks are difficult to trace, as the compilers freely excerpted their material from sources that they mostly do not identify.
Repeated copying by scribes whose knowledge of medical matters varied sometimes introduced mistakes into the text, including garbled or corrupt versions of names of body parts, sicknesses, and medicinal ingredients Keiser ; Benskin ; Norri a , b. These treatises derive from the university tradition, comprising works written by classical and medieval medical authorities.
Although different copies of the same work may show instances of simplification or condensation, academic medical texts underwent far less revision than remedybooks Voigts Especially common in this group are surgical manuals, which are mainly translations from Latin. Earlier studies of Middle English and Early Modern English medical vocabulary have shown that the terminology employed in surgical manuals differs quite significantly from that found in other types of academic medical writing. There is thus some justification for making a threefold rather than a twofold classification of source material in studies of medical vocabulary in late medieval England.
The corpus collected for DMV comprises medical texts from all three categories discussed above. In terms of manuscript and book pages, surgical manuals make up the single largest group, with some pages taken from such works. The other types of academic treatise, which include general compendia on medicine as well as tracts devoted to specific subjects e.
Remedybooks are the smallest section of the corpus, running to circa pages. As noted above, the medical terminology found in remedybooks mostly consists of common words that also occur in surgical and other types of academic treatise. Some of the recipes have in fact been excerpted from academic works, but the technical terminology of the latter has been simplified or omitted in the process Getz Owing to the basic nature of the vocabulary employed, remedybooks, unlike academic works, contain few explicit comments on the meanings of terms.
In lexical studies, there is thus a good case for concentrating on academic and surgical works rather than remedybooks. The corpus contains unedited manuscripts, editions of Middle English medical works, and early printed books. One of the aims when collecting the material was to include a large number of unedited manuscripts.
It was expected that previously untapped manuscript material would bring to light many words and phrases as yet unrecorded in the existing historical dictionaries of English. Of the 72 different medical treatises in the corpus, 38 are found in manuscripts, 18 in editions, and 16 in early printed books. The gathering of the corpus began in the late s, and the last texts were selected for it at the beginning of the present millennium. In the reading programme, the greatest challenge was posed by handwritten manuscripts, ordered from the various libraries as microfilms. In the treatment of the data, methods of optical character recognition could not be used, because they have little precision for handwritten text Sonkusare and Sahu The methods of ORC have developed in recent times but there is still room for further improvement.
The ER Entity—Relationship model is an established conceptual modelling method for representing concepts, their mutual relationships, and the properties of concepts and relationships. A well-designed ER schema provides a sound framework for the structure of the database of the underlying application domain. The basic primitives of the ER model are the entity type also called concept , relationship, and attribute.
A concept involves a set of entities that are instances of the concept. A relationship is associated with one or more concepts, and attributes are attached to concepts or relationships. A relationship also involves cardinality constraints that determine whether one or more instances of concepts participate in the relationship. We use the ER model to represent the concepts and their relationships pertaining to the present project. First, ER schema fragments are given to illustrate the data structures needed in different use cases.
Then, the fragments are collected into one ER schema, in terms of which the structure of the database is formed. Below, the attributes are not given in the visual representation so as to keep the illustrations compact. TERM, for example, contains almost twenty attributes and their visual representation would make the schema large and complex to follow. The malady in maner ys lyke wylde fyyr and yt wyll sprynge owte and ryn abowte a man.
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Fistula is an hollowe sore, and it is so called bycause it hath an holownes lyke a pype. For the same cause the Grecians haue named it syrynges. For locating the passage in the original work, information about the page or leaf in question is essential. The unedited manuscripts in the corpus were either paginated each page numbered or foliated each leaf numbered.
As for edited manuscripts, the most convenient guide to the relevant passage is the page number of the edition, followed by the line where the quotation begins. Early printed books were assembled from gatherings of leaves, each gathering signed by a letter of the Latin alphabet, with leaves subsequent to the first carrying a numerical suffix, e. For each quotation, the word or words of interest therein needed to be identified.
English spelling was not yet standardized, and the same word could be spelt in a variety of ways e. Some of the terms for body parts, sicknesses, medicines, and instruments are said to be used in languages other than English by the medieval authors. Such words were also collected from the corpus for research purposes, although the dictionary itself lists only words that appear in an English context, without being labelled foreign.
Some of the variant spellings of a word occurred frequently in the quotations, others only once. For the word heart , for example, the list of variant spellings is the following: ert , hart , harte , heart , hearte , hert , herte , hertte , horte. In historical dictionaries, it is customary to indicate separately whether a particular spelling variant is a singular or plural form. Owing to limitations of space, printed dictionaries do not usually give all the regular plural forms ending in -s if there are many of them and the list of singular forms already contains the same spelling variant without the plural -s see e.
Lewis Whether a particular variant is a singular e. The need to list the variant separately in the printed dictionary is stated, as is the need to provide a cross-reference from the variant to the dictionary headword TERM in cases where the two are quite different in form e. Occasionally, only the singular or the plural form of the word was used in a particular meaning.
For indicating relations between individual meanings and grammatical number, the concept NUMBER was included in the schema.
The different spelling variants of basically the same word in the corpus were placed under a particular headword TERM. The form chosen as the headword was the one closest to the corresponding modern term if any. Because of polysemy, multiple placement was common. As appears from above, one of the most polysemous words in late medieval medical writings was bag , used of body parts senses 5, 6, 7 , sicknesses 8, 9 , instruments 1, 4 , and medicines 2, 3 alike. The nineteen categories include groups such as French loanwords, Latin loanwords, English suffix formations, and English prefix formations, to cite but a few examples.
French and Latin. Another category group consists of derivatives of English origin, which comprise English prefix and suffix formations. Now that the different concepts and their relationships have been discussed in the light of three fragments of the ER schema Figs. The fragments are integrated based on the common concepts found in them. During the years —, the Paradox database created by the first author was used to collect and maintain dictionary data. The database structure became complicated as new items of information were incorporated, and redesign was necessary to improve the usability and performance of the database.
At the same time, there arose a need to use a modern graphical user interface and enable the generation of a printed version of the dictionary. Three student project teams Poranen ; Kajaste and Poranen ; Poranen developed the DMV application during the years — under the supervision of the authors of the present paper. The second team refactored implementation to use the CakePHP framework and redesigned the user interface. The third team enhanced the functionalities of the system and made possible the generation of the printed version of the dictionary from selected parts of the database.
The database structure was gradually moulded into its current form during these projects. The user inserts the variant s of interest into the table, specifying whether they are used as English words ENG or said to be foreign, e. Greek GRE. As in Fig. The medical term sometimes occurs in the margin of the manuscript or book, as a pointer to the adjacent passage. Such location outside the main text is also indicated in the table. A screenshot of the user interface for storing variants and information on them. For adding a new sense to the database, the screen is simpler and involves three types of information.
In a specialized dictionary, the description of the meaning of a word or phrase often needs to be fuller than in a general-purpose dictionary. In the latter kind of work, it may be enough to state that save was a medicinal paste used internally in the treatment of wounds and injuries, but medical historians and editors of medieval medical treatises would surely also like to know the ingredients and the method of preparing the medicine.
Such lengthy or encyclopedic descriptions would, however, be unwieldy in a comprehensive list summarizing the senses that medical words had during the period investigated. This is why the new senses that are stored in the database are divided into two main parts. When senses are browsed, only the former are shown on the list. The user adding a new sense further needs to specify whether it is a top-level root sense or has a parent sense above it in the semantic classification cf. It is possible to carry out searches on variants, quotations, terms, and senses stored in the database.
The searches for variants, quotations, and senses are straightforward in that they involve typing a spelling variant, key word, or several key words in the search box. The search for terms offers a wider variety of possibilities, as there are more search parameters. The search view looks like the view for adding new terms in Fig. The relevant hits appear as a list, where clicking an item results in fuller information on it, found on a screen similar to the one used for browsing terms Fig. That screen is also used for adding a reference to books or articles which are relevant for understanding the medieval use of the term the buttons at the bottom of the screen, not shown in Fig.
DMV was published in two volumes, altogether circa pages. The database that provided the basis for the printed work contains more information than the latter, for which a selection had to be made of the 23, quotations and 37, variants including 16, different variants because of restrictions of space. The variants that the medieval writers signalled as belonging to a foreign language found little place in the published volumes.
The total number of terms created in the process of compiling the dictionary is 12,, coupled with senses.
The resulting term-sense pairs ran to 14, items. Linked to individual terms, references to different background sources are provided. The printed dictionary called for some manual editing after the necessary items of information had been transferred into it from the database. Long quotations had to be shortened, keeping intact the central parts that threw light on the meaning and use of the term. In the list of combinations built round a particular headword, it was not infrequently the case that two or more compounds or phrases had an identical meaning.
In order to avoid unnecessary repetition in such cases, the sense was given in full only when it first appeared on the alphabetical list, with subsequent references to that definition. The digital application of DMV is implemented on top of a relational database.
Markup languages maintain the original hierarchical structure of the lexicon entries, whereas in the context of the feature-based model, advanced manipulation needs such as recursive queries and flexible factoring are emphasized. In the following, we will introduce these models and investigate how our system takes such questions into account. Structurally, an XML document forms a hierarchy consisting of nested elements in terms of which the nested content of a lexical entry can be conveniently represented.
XML does not require any predefined structure, which means that entries may vary from each other structurally. This has been an important property in developing digital dictionaries, because different sources printed dictionaries have different structures and ways of ordering the lexical entities. In other words, the entries can be first digitalized and the structures can be derived and integrated later on. In representing the structure, a grammatical approach DTD, i. However, if the entries and the related elements vary from each other considerably in terms of structure, then the corresponding DTD is loose, i.
In other words, this kind of DTD does not determine the structure of the dictionary entries strictly. This has been observed for example in the developing of the electronic version of OED Weiner DTD and the XML schema can be seen as a schema-level description which corresponds to the relational schema in the sense that they all determine how the actual data are organized. An XML structure is a hierarchy, but lexical data also contains other kinds of relationships.
For expressing such relationships, external references are used in XML and they can be seen to correspond to foreign key references in relational databases. At the instance level, the data represented in relational databases can also be viewed hierarchically. The use case given in Sect. It would also be possible to construct other kinds of hierarchical views. A value may be complex, which means that an attribute-value pair can represent a hierarchical structure.
Attribute-value pairs can be manipulated by logical operations for uniting and restructuring them. This makes the feature-based model flexible in organizing data into different hierarchical views. We will next introduce how these questions relate to our design and implementation of DMV. Recursive nesting of entities is also essential in DMV , because this kind of relationship appears in connection with senses, terms, and references. In this approach, a nested structure can be stored and then manipulated by a transitive closure algorithm.
Dictionary of Medical Terms - Barron's Educational Series - Literati by Credo
In DMV the transitive closure algorithm is implemented by the host language. Factoring, generally speaking, means a property for reorganizing lexical data into different hierarchies. As noticed in the context of XML above, the DMV data can be reorganized into different hierarchical views, although only one alternative is explicitly presented in the context of the printed version of DMV.
In our work, a similar situation occasionally arose in connection with questions of number, as illustrated in Sect. In practice, such cases were handled by a separate value of an attribute in the Numbers table see Appendix. In the present paper, we have shown how this was done with the ER model. In our modelling of the lexical database for DMV , the standard historical dictionaries of English, in particular MED and OED , were very helpful in suggesting various concepts for inclusion. The issues that have been addressed are likely to come up in the compilation of most dictionaries that aim at a wide coverage of the vocabulary of a special field during a certain period in history.
The requirements posed on the database by a historical specialized dictionary turned out to be partly the same as for more extensive historical dictionaries, partly particular to works devoted to scientific or medical vocabulary. In alphabetical dictionaries, the selection and arrangement of headwords is one of the most basic questions. In particular, the placing of extended units or phrases built around a specific word should follow principles that are clear to the users. Thus, for example, under the entry for melancholy n. In the OED arrangement, the headword of the entire entry occurs as the first element of the compound.
In the DMV database and printed work, a different approach was adopted. In the treatment of specialized terminology, the parent term approach has the advantage of giving the browser an immediate idea of how the phenomenon in question was classified in contemporary medical or scientific writings. The combinations placed under the term blood in the database comprise 89 phrases, and a mere glance at the list on the screen shows that one important basis of classification was the purity e. The most prolific generator of combinations in our corpus was the term water , with no fewer than extensions, mostly names of medicinal waters e.
As seen from the vena cava example and the 29 terms for epilepsy cited in Sect. There was no general agreement about the naming of individual organs, conditions, instruments, or medicines. Some writers observe that the phenomenon is in fact common in medicine Pilegaard ; Landau For handling questions of synonymy, the database structure proved especially useful. The senses of the words and phrases were stored as independent units. Whenever a term appeared carrying a sense already recorded for some other term, it was simply linked to that existing sense.
Because of this policy, the definitions of the medieval synonyms are worded identically in the database, which makes it easy to find all the different names that were applied to specific medical referents in the medieval material. Besides laying the foundation for a dictionary, the database can thus also be used as a thesaurus.
It has to be stated, though, that the thesaurus aspect still calls for further developing. The senses were stored in the database as they came up in the corpus texts, and a total picture of the sense relationships was difficult to form at that stage. It was not infrequently difficult to decide what would be the parent sense, if any, for a new sense, and sometimes a suitable parent sense only appeared after the lower-level sense was already there.
In a fully fledged thesaurus, individual senses are grouped under larger categories, and the principles of such categorization need further elaboration for Middle English and Early Modern English medical vocabulary. Further distinctions were made according to the organs where the putrefaction or increase of the humour took place see e.
Bynum and Nutton ; Demaitre The role of the bodily humours or organs does not emerge from the treatment of the semantic category of fever in the entry An anonymous reviewer for LRE makes the pertinent suggestion that book illustrations and manuscript images might be considered for inclusion in the dictionary database in cases where they illuminate the medieval use of the term.
Sometimes the meaning of a medieval term remained uncertain or unclear in spite of a close scrutiny of the context s in which it appeared. By the completion of the project, many duplicated senses had arisen this way: one furnished with a question mark, the other without it. It would have been more economical to have just one sense and a separate marker for the uncertain instances.
Similar considerations apply to errors in the corpus texts. For example, in one treatise the word fistula is erroneously used for the uvula. In historical dictionaries, the foreign and adapted forms of loanwords are often treated as separate entries, but not invariably so. Gangrena and gangrene , as well as the earlier cancrena and cancrene , are all found under gangrene n.
In the DMV database and printed dictionary, the original and the modified versions are regularly listed as separate terms, with a cross-reference from one to the other. Unlike historical dictionaries, including the printed DMV , the database also contains all the words and phrases that the medieval writers assigned to a foreign language using formulae such as the ones cited in Sect. Incompletely naturalized forms have been something of a headache for lexicographers see e.
Lewis ; Gilliver , but their importance for the development of the lexical field should not be underestimated. Many of the terms that some writers singled out as belonging, for example, to Latin or French were used without any such comment by others. The information in the database enables a more comprehensive study of the history of the word or phrase especially in cases where the term has only gradually lost its foreign status in English medical writing.
References to background sources relevant to specific terms are a highly useful feature in historical specialized dictionaries such as DMV. Many of the lexical items occurring in medieval medical works go back to Latin or Greek, and scholars studying those two languages and medical treatises written in them have often discovered information that is missing from the English texts. Furthermore, medical historians sometimes disagree between themselves as to the exact referent of the medieval term, a good example being the cells or cellules of the brain Norri For those consulting the dictionary, it is useful to be aware of the differing opinions.
In the database, references to background sources were linked to terms, but in many instances they could also have been linked to senses because of the prevalence of synonymy in the corpus texts. If a certain article or book throws light on the meaning of a specific term, it is also likely to illuminate the meanings and uses of some of its synonyms. In future development of the database structure, the relationship between background references, terms, and senses deserves further attention.
The explicit classification of each headword into semantic, word-formational, and etymological categories is a feature that is usually absent from dictionaries. The presence of such data in DMV will be useful for lexicologists interested in the origins and use of medieval medical words and phrases, especially when entire lexical fields are being investigated.
For example, it is possible to generate a list of all the terms that were created by English writers with the help of suffixes, or a list of all the English words that were used metaphorically to denote a sickness, body part, medicine, or instrument. Functions enabling a systematic pooling of certain types of lexical items proved most helpful in a recent article on translation from Latin and French as a source of new medical terms in late medieval England Norri b. Any information system or software development project is finally evaluated through its use cases, i. In a software development project, the most serious problems typically follow mistakes in modelling an application domain or a universe of discourse.
In other words, if there is an error in the underlying conceptual structure, this is reflected in the whole application and causes failures in various use cases. In the present electronic dictionary, all use cases succeeded well, which also means that the conceptual model and database works well.
In practice, this is also due to the carefully designed iterative processing. The database structure that was created for DMV could, with minor modifications, be applied to the historical study of vocabularies of other special fields than medicine. The history of scientific and medical writing is attracting increasing attention in many languages, and the questions that came up in the creation of our database are likely to emerge in other languages as well.
A vast number of English medical terms, be they medieval or more modern, have their origins in Latin or Greek, and even Arabic is relevant for understanding the story behind some of them. Perhaps one day scholars interested in the development of medical vocabulary will have available to them a set of similarly structured databases for various languages, with mutual links between them. That would mean a significant widening of perspective not just in lexical matters but also in the history of various medical ideas.
The authors are currently looking into the possibility of producing a published version of the DMV database. At present, it is possible for interested scholars to gain access to the data for research purposes by writing to the corresponding author. The Dictionary of medical vocabulary in English, — project was made possible by financial support from the Academy of Finland and the Finnish Cultural Foundation. We are greatly indebted to Paul Schaffner for a wealth of information on the digitization of the Middle English dictionary.
We would also like to thank the three anonymous reviewers for their suggestions and observations. Skip to main content Skip to sections. Advertisement Hide. Download PDF. Language Resources and Evaluation pp 1—29 Cite as. Digitization of data for a historical medical dictionary. Open Access. First Online: 04 June In an ER schema, a concept is represented by a rectangle, an attribute by an oval, and a relationship by a rhomb. In Fig. In it, three concepts and their mutual relationships are represented.
There is also a relationship within TERM. This kind of relationship is called a recursive relationship and it can be used to express relationships of sub- and super-concepts. Open image in new window. The texts in the corpus were subjected to a systematic reading programme, during which any occurrences of words that were potential candidates for inclusion in the dictionary were noted down.
Those items that on closer inspection were judged to be useful additions to the lexical inventory e. The first stage in the storing process was the creation of a QUOTE containing the word and some of the passage surrounding it in the medieval work. The length of the quotation varied depending on how much of the context was illuminating for the Middle English or Early Modern English use of the word. The following three quotations were stored in the database because they provide useful definitions of the common medical terms shingles , polyp , and fistula , respectively cf.
The fragment of the ER schema in Fig. In medieval medical vocabulary, polysemy was rife. It is therefore important to specify the meaning in which the word is used in a particular quotation. The following nine pairs, for example, were created to cover the different meanings of the word bag that emerged in the course of the lexical analysis: 1. The database consists of tables that correspond to the concepts and relationships of the ER-model.
A table involves attributes properties having different roles. All the tables involve the id attribute primary key that identifies the instances rows of the table. An arrow from a foreign key e. The rest of the attributes contain actual data. We do not introduce the data attributes in detail here, but next we will illustrate their content by the application of DMV. In what follows, the database is described from the point of view of those who use it for storing, browsing, or searching information.
The different use cases set requirements on the functionalities of the system and on the kinds of information that need to be included therein. The main page of the database, shown in Fig. We will discuss the most central functionalities in an order that roughly corresponds to the presentation of the concepts in Sect. The screenshot in Fig. The information that is stored comprises the following items: 1 an eight-character shorthand reference to the text in question e. Section 4. Each English-language variant needs to be placed under a particular dictionary headword and the sense that it carries in the quotation needs to be stated.
For doing this, each line of variants ends with a thought bubble, whose clicking takes one to the comprehensive list of term-sense pairs.
If no suitable term or sense can be found, they will need to be created in the manner explained below. How a new term or dictionary headword is created appears from the screenshot in Fig. A distinction is thus made between terms already listed in the major historical dictionaries covering the period — and terms whose first attested occurrence comes from the corpus texts.
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