Biomedical subjects

Susan Perkins

Publications and source records attributed to Susan Perkins.

4 recordsLinked to original sources

PubMed2004

A simple error classification system for understanding sources of error in automatic speech recognition and human transcription.

OBJECTIVES: To (1) discover the types of errors most commonly found in clinical notes that are generated either using automatic speech recognition (ASR) or via human transcription and (2) to develop efficient rules for classifying these errors based on the categories found in (1). The purpose of classifying errors into categories is to understand the underlying processes that generate these errors, so that measures can be taken to improve these processes. METHODS: We integrated the Dragon NaturallySpeaking v4.0 speech recognition engine into the Regenstrief Medical Record System. We captured the text output of the speech engine prior to error correction by the speaker. We also acquired a set of human transcribed but uncorrected notes for comparison. We then attempted to error correct these notes based on looking at the context alone. Initially, three domain experts independently examined 104 ASR notes (containing 29,144 words) generated by a single speaker and 44 human transcribed notes (containing 14,199 words) generated by multiple speakers for errors. Collaborative group sessions were subsequently held where error categorizes were determined and rules developed and incrementally refined for systematically examining the notes and classifying errors. RESULTS: We found that the errors could be classified into nine categories: (1) announciation errors occurring due to speaker mispronounciation, (2) dictionary errors resulting from missing terms, (3) suffix errors caused by misrecognition of appropriate tenses of a word, (4) added words, (5) deleted words, (6) homonym errors resulting from substitution of a phonetically identical word, (7) spelling errors, (8) nonsense errors, words/phrases whose meaning could not be appreciated by examining just the context, and (9) critical errors, words/phrases where a reader of a note could potentially misunderstand the concept that was related by the speaker. CONCLUSIONS: A simple method is presented for examining errors in transcribed documents and classifying these errors into meaningful and useful categories. Such a classification can potentially help pinpoint sources of such errors so that measures (such as better training of the speaker and improved dictionary and language modeling) can be taken to optimize the error rates.

Automation↗

PubMed2004

Human monoclonal antibody to hepatitis C virus E1 glycoprotein that blocks virus attachment and viral infectivity.

Human antibodies elicited in response to hepatitis C virus (HCV) infection are anticipated to react with the native conformation of the viral envelope structure. Isolation of these antibodies as human monoclonal antibodies that block virus binding and entry will be useful in providing potential therapeutic reagents and for vaccine development. H-111, an antibody to HCV envelope 1 protein (E1) that maps to the YEVRNVSGVYH sequence and is located near the N terminus of E1 and is able to immunoprecipitate E1E2 heterodimers, is described. Binding of H-111 to HCV E1 genotypes 1a, 1b, 2b, and 3a indicates that the H-111 epitope is highly conserved. Sequence analysis of antibody V regions showed evidence of somatic and affinity maturation of H-111. Finally, H-111 blocks HCV-like particle binding to and HCV virion infection of target cells, suggesting the involvement of this epitope in virus binding and entry.

Amino Acid Sequence↗

PubMed2004

A comparative approach to understanding causes and consequences of mollusc-digenean size relationships: a case study with Allocreadiid trematodes and Cyclocalyx clams.

Allocreadiid flukes often parasitize and castrate sphaeriid freshwater clams. The effects of parasitic castrators on host population life history can lead to earlier reproductive onset, changes in body size, or changes in the number of reproductive events per year. However, little is known about whether species- or clade-level traits are associated with parasite prevalence. In this study, we examine if phenotypic effects, e.g., size change, seen at the population level, sort to the species or clade level. To answer this question, we determined if different-sized host species in the ecologically important, widespread, and common sphaeriid subgenus Cyclocalyx have different prevalences of allocreadiid infection. After showing that large species are more than 12 times more likely to have patent infections than small species, we examined the evolution of size within Cyclocalyx lineages. Transitions from large size to small size or vice versa have occurred at least twice and probably many times during lineage diversification, perhaps relating to trade-offs between clutch size and parasite risk. Finally, based on existing data, we show that it is unlikely that age and body size are correlated; therefore, a simple age-exposure model is not a sufficient explanation for parasite prevalence in this clade.

Animals↗

PubMedDate not supplied

Implementing a point-of-care testing program in the critical care setting.

Clearly, there are important reasons for both the critical care area and the laboratory to improve efficiencies wherever possible and at the same time maintaining or improving quality. POCT, when implemented in a way that fits the individual system, can accomplish both of those objectives. By all accounts, the trend toward providing POCT will continue, particularly in the critical care units where TAT of the most important STAT tests is of the utmost importance in providing the best possible patient care. To support that trend, critical care clinicians need to closely work with experts in laboratory medicine to bring the expertise of the laboratory to the patient's bedside, where quick and accurate results are needed. By working together, critical care clinicians and laboratorians can create quality POCT programs in the critical care unit, which can meet the needs of both clinicians and laboratorians and, most of all, the critically ill patients in our care.

Critical Care↗