Biomedical subjects

Rebecca S Crowley

Publications and source records attributed to Rebecca S Crowley.

6 recordsLinked to original sources

PubMed2004

Implementation and evaluation of a negation tagger in a pipeline-based system for information extract from pathology reports.

We have developed a pipeline-based system for automated annotation of Surgical Pathology Reports with UMLS terms that builds on GATE--an open-source architecture for language engineering. The system includes a module for detecting and annotating negated concepts, which implements the NegEx algorithm--an algorithm originally described for use in discharge summaries and radiology reports. We describe the implementation of the system, and early evaluation of the Negation Tagger. Our results are encouraging. In the key Final Diagnosis section, with almost no modification of the algorithm or phrase lists, the system performs with precision of 0.84 and recall of 0.80 against a gold-standard corpus of negation annotations, created by modified Delphi technique by a panel of pathologists. Further work will focus on refining the Negation Tagger and UMLS Tagger and adding additional processing resources for annotating free-text pathology reports.

Algorithms↗

PubMed2003

Using contextual design to identify potential innovations for problem based learning.

We report on the use of Contextual Design (CD) to develop models of the information management, resource integration, and collaborative processes of medical students in problem-based learning groups. CD is a modified ethnographic technique designed to provide a detailed understanding of the user's needs. Although the technique has been used in non-healthcare related fields, there is limited published data on the application of CD within healthcare settings. In this pilot study, we evaluated the feasibility of the CD methodology for this domain, developed an initial set of CD models, and formulated a series of design ideas based on the data. The study helps to clarify the effectiveness and feasibility of CD as well as the limitations for using this method in health-related domains.

Cooperative Behavior↗

PubMed2003

A general architecture for intelligent tutoring of diagnostic classification problem solving.

We report on a general architecture for creating knowledge-based medical training systems to teach diagnostic classification problem solving. The approach is informed by our previous work describing the development of expertise in classification problem solving in Pathology. The architecture envelops the traditional Intelligent Tutoring System design within the Unified Problem-solving Method description Language (UPML) architecture, supporting component modularity and reuse. Based on the domain ontology, domain task ontology and case data, the abstract problem-solving methods of the expert model create a dynamic solution graph. Student interaction with the solution graph is filtered through an instructional layer, which is created by a second set of abstract problem-solving methods and pedagogic ontologies, in response to the current state of the student model. We outline the advantages and limitations of this general approach, and describe it's implementation in SlideTutor - a developing Intelligent Tutoring System in Dermatopathology.

Artificial Intelligence↗

PubMed2003

The Virtual Slide Set - a curriculum development system for digital microscopy.

We describe the development of a Virtual Slide System for creating and viewing clinico-pathologic cases with embedded interactive digital microscopy. The system supports rich text-to-image annotation, including (1) hotlinks of text descriptions that move the student to the correct part of the slide, and (2) annotations such as arrows and circles that appear on the Virtual Slide on request. The interface can be configured by the student to alter the degree of guidance the system provides. The authoring layer provides a graphical user interface to authors for creating new case sets, cases, questions, and annotated virtual slides, which are saved to a database and automatically added to the Virtual Slide homepage. The system has been used in two pilot studies at the University of Pittsburgh.

Histology↗

PubMed2003

A knowledge-based approach to information extraction from surgical pathology reports.

We describe the development of a prototype system for knowledge-based information extraction from surgical pathology reports. The current system includes abstract problem solving methods and a frame-based knowledge representation of body parts, procedures, diseases, and findings for prostate and breast cases. The system currently extracts the organ, procedure, and diagnoses, and sets an agenda of goals for further processing. A potential advantage of this approach is the ability to increase specificity of information extraction.

Artificial Intelligence↗

PubMedDate not supplied

Development of visual diagnostic expertise in pathology -- an information-processing study.

OBJECTIVE: To identify key features contributing to trainees' development of expertise in microscopic pathology diagnosis, a complex visual task, and to provide new insights to help create computer-based training systems in pathology. DESIGN: Standard methods of information-processing and cognitive science were used to study diagnostic processes (search, perception, reasoning) of 28 novices, intermediates, and experts. Participants examined cases in breast pathology; each case had a previously established gold standard diagnosis. Videotapes correlated the actual visual data examined by participants with their verbal "think-aloud" protocols. MEASUREMENTS: Investigators measured accuracy, difficulty, certainty, protocol process frequencies, error frequencies, and times to key diagnostic events for each case and subject. Analyses of variance, chi-square tests and post-hoc comparisons were performed with subject as the unit of analysis. RESULTS: Level of expertise corresponded with differences in search, perception, and reasoning components of the tasks. Several discrete steps occur on the path to competence, including development of adequate search strategies, rapid and accurate recognition of anatomic location, acquisition of visual data interpretation skills, and transitory reliance on explicit feature identification. CONCLUSION: Results provide the basis for an empirical cognitive model of competence for the complex tasks of microscopic pathology diagnosis. Results will inform the development of computer-based pedagogy tools in this domain

Analysis of Variance↗