Thesis--Indiana University. / Vita. Includes bibliographical references (leaves 142-146).

Thesis--Rutgers University. / Vita. Photocopy of typescript. Ann Arbor: University Microfilms, 1977.--21 cm. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 63-67).

An overview of resources and techniques for literature searching in mental health

Artificial Intelligence Lab, Department of MIS, Univeristy of Arizona / In an effort to assist medical researchers and professionals in accessing information necessary for their work, the A1 Lab at the University of Arizona is investigating the use of a natural language processing (NLP) technique called noun phrasing. The goal of this research is to determine whether noun phrasing could be a viable technique to include in medical information retrieval applications. Four noun phrase generation tools were evaluated as to their ability to isolate noun phrases from medical journal abstracts. Tests were conducted using the National Cancer Institute's CANCERLIT database. The NLP tools evaluated were Massachusetts Institute of Technology's (MIT's) Chopper, The University of Arizona's Automatic Indexer, Lingsoft's NPtool, and The University of Arizona's AZ Noun Phraser. In addition, the National Library of Medicine's SPECIALIST Lexicon was incorporated into two versions of the AZ Noun Phraser to be evaluated against the other tools as well as a nonaugmented version of the AZ Noun Phraser. Using the metrics relative subject recall and precision, our results show that, with the exception of Chopper, the phrasing tools were fairly comparable in recall and precision. It was also shown that augmenting the AZ Noun Phraser by including the SPECIALIST Lexicon from the National Library of Medicine resulted in improved recall and precision.

Artificial Intelligence Lab, Department of MIS, University of Arizona / This research investigated the application of techniques successfully used in previous information retrieval research, to the more challenging area of medical informatics. It was performed on a biomedical document collection testbed, CANCERLIT, provided by the National Cancer Institute (NCI) , which contains information on all types of cancer therapy. The quality or usefulness of terms suggested by three different thesauri, one based on MeSH terms, one based solely on terms from the document collection, and one based on the Unified Medical Language System UMLS Metathesaurus, was explored with the ultimate goal of improving CANCERLIT information search and retrieval. Researchers affiliated with the University of Arizona Cancer Center evaluated lists of related terms suggested by different thesauri for 12 different directed searches in the CANCERLIT testbed. The preliminary results indicated that among the thesauri, there were no statistically significant differences in either term recall or precision. Surprisingly, there was almost no overlap of relevant terms suggested by the different thesauri for a given search. This suggests that recall could be significantly improved by using a combined thesaurus approach.

Artificial Intelligence Lab, Department of MIS, University of Arizona / This paper discusses several data mining algorithms and techniques that we have developed at the University of Arizona Artificial Intelligence Lab.We have implemented these algorithms and techniques into several prototypes, one of which focuses on medical information developed in cooperation with the National Cancer Institute (NCI) and the University of Illinois at Urbana-Champaign.We propose an architecture for medical knowledge information systems that will permit data mining across several medical information sources and discuss a suite of data mining tools that we are developing to assist NCI in improving public access to and use of their existing vast cancer information collections.

Thesis (Ph. D.)--Florida State University, 1989. / Includes bibliographical references.

Research paper (M.L.I.S.)--Victoria University of Wellington, 2009. / Includes bibliographical references.

Thesis (Ph. D.)--Florida State University, 1989. / Includes bibliographical references.

As the practice of integrative medicine becomes more common, it is important for library science professionals to understand the research needs of integrative medicine professionals in order to best provide resources and services to this population. This paper surveys integrative medicine professionals affiliated with the four North Carolina academic programs and centers for integrative medicine. The results of this study indicate that this population may need more targeted library services due to the difficulty in finding information in this field.