Abstract
RadOnc is a prototype hypermedia program designed for the resident physician which integrates a radiation oncology clinical database with reference information. Basic and clinical science information relevant to radiation oncology with pertinent literature reviews are linked to patient records which contain a clinical summary of the presentation, treatment and results. RadOnc's features include a dictionary, search capability, navigational aids, information printing and archiving, and graphics, linkage and updating tools.
Abstract
Previous research has shown that within the domain of medical journal abstracts the statistical distribution of words is neither random nor uniform, but is highly characteristic. Many words are used mainly or solely by one medical specialty or when writing about one particular level of description. Due to this regularity of usage, automatic classification within journal abstracts has proved quite successful. The present research asks two further questions. It investigates whether this statistical regularity and automatic classification success can also be achieved in medical textbook chapters. It then goes on to see whether the statistical distribution found in textbooks is sufficiently similar to that found in abstracts to permit accurate classification of abstracts based solely on previous knowledge of textbooks. 14 textbook chapters and 45 MEDLINE abstracts were submitted to an automatic classification program that had been trained only on chapters drawn from a standard textbook series. Statistical analysis of the properties of abstracts vs. chapters revealed important differences in word use. Automatic classification performance was good for chapters, but poor for abstracts.
Concepts in basic and clinical medical science cover a wide range of levels of description, from the subatomic level to the level of the patient as a whole. Medical language may have usage regularities consistent with this hierarchical nature of medical knowledge. Preliminary studies of word occurrence in abstracts drawn from three medical journals representing three broadly defined levels of description (chemical system, physiologic system, and patient as a whole) demonstrated a nonuniform word usage, with many words unique to one or another journal. In this present study, word occurrence was examined in an expanded pool of medical text consisting of sixteen textbooks representing ten different levels of description: atom/ion, micromolecule, macromolecule, organelle, cell, tissue, organ, physiologic system, major body part (or multiple physiologic systems) and patient as a whole. Word usage was found to be nonuniform, with many words unique to specific levels. The presence of such usage regularities may provide a basis for facilitating the automatic classification and retrieval of medical text.
MacPharmacy is a relational database built as an adjunct to RadOnc, a hypermedia-based physician workstation in the domain of radiation oncology. Conceived originally as a RadOnc module for chemotherapeutic agents, the MacPharmacy database contains information on a large selection of drugs which can be accessed by a variety of users. Information on generic and trade names, pharmacodynamics, indications, and dosage is linked to RadOnc disease descriptions and patient records which contain a clinical summary of the presentation, treatment and results. MacPharmacy's features include data table addition and updating and a customizable user interface that can be linked to other applications. Due to the scarcity of Macintosh-based pharmacy databases, MacPharmacy fills an information gap for clinically-oriented Macintosh users.
'/%3e%3c/defs%3e%3cpath fill='%23012169' d='M0 0h10080v5040H0z'/%3e%3cpath stroke='%23fff' stroke-width='.6' d='m0 0 6 3m0-3L0 3' clip-path='url(%23b)' transform='scale(840)'/%3e%3cpath stroke='%23e4002b' stroke-width='.4' d='m0 0 6 3m0-3L0 3' clip-path='url(%23c)' transform='scale(840)'/%3e%3cpath stroke='%23fff' stroke-width='840' d='M2520 0v2520M0 1260h5040'/%3e%3cpath stroke='%23e4002b' stroke-width='504' d='M2520 0v2520M0 1260h5040'/%3e%3cg fill='%23fff'%3e%3cuse xlink:href='%23d' x='2520' y='3780'/%3e%3cuse xlink:href='%23a' x='7560' y='4200'/%3e%3cuse xlink:href='%23a' x='6300' y='2205'/%3e%3cuse xlink:href='%23a' x='7560' y='840'/%3e%3cuse xlink:href='%23a' x='8680' y='1869'/%3e%3cuse xlink:href='%23e' x='8064' y='2730'/%3e%3c/g%3e%3c/svg%3e)