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Biomedical subjects

C Friedman

Publications and source records attributed to C Friedman.

At least 37 records · Page 2Linked to original sources

Coding neuroradiology reports for the Northern Manhattan Stroke Study: a comparison of natural language processing and manual review.

Automated systems using natural language processing may greatly speed chart review tasks for clinical research, but their accuracy in this setting is unknown. The objective of this study was to compare the accuracy of automated and manual coding in the data acquisition tasks of an ongoing clinical research study, the Northern Manhattan Stroke Study(NOMASS). We identified 471 neuroradiology reports of brain images used in the NOMASS study. Using both automated and manual coding, we completed a standardized NOMASS imaging form with the information contained in these reports. We then generated ROC curves for both manual and automated coding by comparing our results to the original NOMASS data, where study in investigators directly coded their interpretations of brain images. The areas under the ROC curves for both manual and automated coding were the main outcome measure. The overall predictive value of the automated system (ROC area 0.85, 95% CI 0.84-0.87) was not statistically different from the predictive value of the manual coding (ROC area 0.87, 95% CI 0.83-0.91). Measured in terms of accuracy, the automated system performed slightly worse than manual coding. The overall accuracy of the automated system was 84% (CI 83-85%). The overall accuracy of manual coding was 86% (CI 84-88%). The difference in accuracy between the two methods was small but statistically significant (P = 0.026). Errors in manual coding appeared to be due to differences between neurologists' and nueroradiologists' interpretation, different use of detailed anatomic terms, and lack of clinical information. Automated systems can use natural language processing to rapidly perform complex data acquisition tasks. Although there is a small decrease in the accuracy of the data as compared to traditional methods, automated systems may greatly expand the power of chart review in clinical research design and implementation.

Brain↗

Prevention of cerebrospinal fluid rhinorrhea in neurotologic surgery.

OBJECTIVE: To determine the efficacy and safety of quick-setting hydroxyapatite cement in eliminating cerebrospinal fluid (CSF) rhinorrhea following neurotologic surgery. STUDY DESIGN: A prospective study of 40 consecutive patients undergoing neurotologic surgery in whom the dura was opened. SETTING: All patients were treated as hospital inpatients at a tertiary referral center. PATIENTS: 25 men and 15 women between the ages of 20 and 72 years (mean age 51 years) underwent neurotologic surgery at the parent institution. INTERVENTION: Various neurotologic procedures were performed for the resection of 25 acoustic tumors, 5 meningiomas, 3 glomus tumors, 2 vestibular nerve sections, 2 chordomas, 1 epidermoid tumor, and 1 meningoencephelocele, and for 2 patients referred to our institution with known CSF leaks following acoustic tumor surgery. A new form of quick-setting hydroxyapatite cement, which that hardens within 3 to 5 minutes was used to seal the air cell tracts of the temporal bone in all cases. MAIN OUTCOME MEASURE: The presence of CSF rhinorrhea postoperatively. RESULTS: CSF rhinorrhea occurred in 2 patients following acoustic tumor surgery, the first through an occult air cell tract at the margin of the drilled internal auditory canal, and the second via an oval window fistula 1 month after a translabyrinthine approach. CONCLUSIONS: This form of hydroxyapatite cement appears safe, reliable, effective, and economical for the prevention of CSF rhinorrhea following neurotologic surgery. CSF rhinorrhea cannot be eliminated unless our ability to identify all potential air cell tract communications improves.

Adult↗

A knowledge model for analysis and simulation of regulatory networks.

MOTIVATION: In order to aid in hypothesis-driven experimental gene discovery, we are designing a computer application for the automatic retrieval of signal transduction data from electronic versions of scientific publications using natural language processing (NLP) techniques, as well as for visualizing and editing representations of regulatory systems. These systems describe both signal transduction and biochemical pathways within complex multicellular organisms, yeast, and bacteria. This computer application in turn requires the development of a domain-specific ontology, or knowledge model. RESULTS: We introduce an ontological model for the representation of biological knowledge related to regulatory networks in vertebrates. We outline a taxonomy of the concepts, define their 'whole-to-part' relationships, describe the properties of major concepts, and outline a set of the most important axioms. The ontology is partially realized in a computer system designed to aid researchers in biology and medicine in visualizing and editing a representation of a signal transduction system.

Animals↗

Characterization of nonfunctional V1R-like pheromone receptor sequences in human.

The vomeronasal organ (VNO) or Jacobson's organ is responsible in terrestrial vertebrates for the sensory perception of pheromones, chemicals that elicit stereotyped behaviors among individuals of the same species. Pheromone-induced behaviors and a functional VNO have been described in a number of mammals, but the existence of this sensory system in human is still debated. Recently, two nonhomologous gene families, V1R and V2R, encoding pheromone receptors have been identified in rat. These receptors belong to the seven-transmembrane domain G-protein-coupled receptor superfamily. We sought to characterize V1R-like genes in the human genome. We have identified seven different human sequences by PCR and library screening with rodent sequences. These human sequences exhibit characteristic features of V1R receptors and show 52%-59% of amino acid sequence identity with the rat sequences. Using PCR on a monochromosomal somatic cell hybrid panel and/or FISH, we demonstrate that these V1R-like sequences are distributed on chromosomes 7, 16, 20, 13, 14, 15, 21, and 22 and possibly on additional chromosomes. One sequence hybridizes to pericentromeric locations on all the acrocentric chromosomes (13, 14, 15, 21, and 22). All of the seven V1R-like sequences analyzed show interrupted reading frames, indicating that they represent nonfunctional pseudogenes. The preponderence of pseudogenes among human V1R sequences and the striking anatomical differences between rodent and human VNO raise the possibility that humans may have lost the V1R/VNO-mediated sensory functions of rodents.

Amino Acid Sequence↗

Infection control outside the hospital: developing a continuum of care.

Pressures to limit or eliminate more expensive inpatient care have led t he way to rapidly expanded use of ambulatory care are extended care services. A consensus panel of infection control specialists have devised new recommendations on what can be addressed when infections occur outside the hospital.

Ambulatory Care↗

Limited parsing of notational text visit notes: ad-hoc vs. NLP approaches.

This paper describes the extraction of structured data relevant to glaucoma diagnosis and progression from visit notes typed as "notational text" by ophthalmologists during patient encounters. We compared two text processing systems: a limited pattern matching system called GDP (Glaucoma Dedicated Parser) and MedLEE, a proven natural language processing system which is in routine use encoding findings from chest radiograph and mammogram reports at the New York-Presbyterian hospital's Columbia-Presbyterian Center. We also evaluated the use of GDP as a preprocessor program to transform notational text into constructions recognizable by MedLEE. These systems have been evaluated according to their recall and precision in the particular task of processing a corpus of "notational text" documents to extract information related to glaucoma disease.

Glaucoma↗

A broad-coverage natural language processing system.

Natural language processing systems (NLP) that extract clinical information from textual reports were shown to be effective for limited domains and for particular applications. Because an NLP system typically requires substantial resources to develop, it is beneficial if it is designed to be easily extendible to multiple domains and applications. This paper describes multiple extensions of an NLP system called MedLEE, which was originally developed for the domain of radiological reports of the chest, but has subsequently been extended to mammography, discharge summaries, all of radiology, electrocardiography, echocardiography, and pathology.

Decision Making, Computer-Assisted↗

A method for vocabulary development and visualization based on medical language processing and XML.

A comprehensive controlled clinical vocabulary is critical to the effectiveness of many automated clinical systems. Vocabulary development and maintenance is an important aspect of a vocabulary, and should be linked to terms physicians actually use. This paper presents a method to help vocabulary builders capture, visualize, and analyze both compositional and quantitative information related to terms physicians use. The method includes several components: an MLP system, a corpus of relevant reports and a visualization tool based on XML and JAVA.

Humans↗

Requirements for infrastructure and essential activities of infection control and epidemiology in out-of-hospital settings: a Consensus Panel report.

In 1997 the Association for Professionals in Infection Control and Epidemiology and the Society for Healthcare Epidemiology of America established a consensus panel to develop recommendations for optimal infrastructure and essential activities of infection control and epidemiology programs in out-of-hospital settings. The following report represents the Consensus Panel's best assessment of requirements for a healthy and effective out-of-hospital-based infection control and epidemiology program. The recommendations fall into 5 categories: managing critical data and information; developing and recommending policies and procedures; intervening directly to prevent infections; educating and training of health care workers, patients, and nonmedical caregivers; and resources. The Consensus Panel used an evidence-based approach and categorized recommendations according to modifications of the scheme developed by the Clinical Affairs Committee of the Infectious Diseases Society of America and the Centers for Disease Control and Prevention's Healthcare Infection Control Practices Advisory Committee.

Allied Health Personnel↗

Requirements for infrastructure and essential activities of infection control and epidemiology in out-of-hospital settings: a consensus panel report. Association for Professionals in Infection Control and Epidemiology and Society for Healthcare Epidemiology of America.

In 1997 the Association for Professionals in Infection Control and Epidemiology and the Society for Healthcare Epidemiology of America established a consensus panel to develop recommendations for optimal infrastructure and essential activities of infection control and epidemiology programs in out-of-hospital settings. The following report represents the Consensus Panel's best assessment of requirements for a healthy and effective out-of-hospital-based infection control and epidemiology program. The recommendations fall into 5 categories: managing critical data and information; developing and recommending policies and procedures; intervening directly to prevent infections; educating and training of health care workers, patients, and nonmedical caregivers; and resources. The Consensus Panel used an evidence-based approach and categorized recommendations according to modifications of the scheme developed by the Clinical Affairs Committee of the Infectious Diseases Society of America and the Centers for Disease Control and Prevention's Healthcare Infection Control Practices Advisory Committee.

Aftercare↗

Natural language processing and its future in medicine.

If accurate clinical information were available electronically, automated applications could be developed to use this information to improve patient care and lower costs. However, to be fully retrievable, clinical information must be structured or coded. Many online patient reports are not coded, but are recorded in natural-language text that cannot be reliably accessed. Natural language processing (NLP) can solve this problem by extracting and structuring text-based clinical information, making clinical data available for use. NLP systems are quite difficult to develop, as they require substantial amounts of knowledge, but progress has definitely been made. Some NLP systems have been developed and tested and have demonstrated promising performance in practical clinical applications; some of these systems have already been deployed. The authors provide background information about NLP, briefly describe some of the systems that have been recently developed, and discuss the future of NLP in medicine.

Forecasting↗

Representing genomic knowledge in the UMLS semantic network.

Genomics research has a significant impact on the understanding and treatment of human hereditary diseases, and biomedical literature concerning the genome project is becoming more and more important for clinicians. The Unified Medical Language System (UMLS) is designed to facilitate the retrieval and integration of information from multiple-readable biomedical information resources. This paper describes our efforts to integrate concepts important to genomics research with the UMLS semantic network. We found that the UMLS contains over 30 semantic types and most of the semantic relations that are essential for representing the underlying genomic knowledge. In addition, we observed that the organization of the network was appropriate for representing the hierarchical organization of the concepts. Because some of the concepts critical to the genomic domain were found to be missing, we propose to extend the network by adding six new semantic types and sixteen new semantic relations.

Genome, Human↗

Automating a severity score guideline for community-acquired pneumonia employing medical language processing of discharge summaries.

Obtaining encoded variables is often a key obstacle to automating clinical guidelines. Frequently the pertinent information occurs as text in patient reports, but text is inadequate for the task. This paper describes a retrospective study that automates determination of severity classes for patients with community-acquired pneumonia (i.e. classifies patients into risk classes 1-5), a common and costly clinical problem. Most of the variables for the automated application were obtained by writing queries based on output generated by MedLEE1, a natural language processor that encodes clinical information in text. Comorbidities, vital signs, and symptoms from discharge summaries as well as information from chest x-ray reports were used. The results were very good because when compared with a reference standard obtained manually by an independent expert, the automated application demonstrated an accuracy, sensitivity, and specificity of 93%, 92%, and 93% respectively for processing discharge summaries, and 96%, 87%, and 98% respectively for chest x-rays. The accuracy for vital sign values was 85%, and the accuracy for determining the exact risk class was 80%. The remaining 20% that did not match exactly differed by only one class.

Community-Acquired Infections↗

What do ER physicians really want? A method for elucidating ER information needs.

Prior discharge summaries are a critical source of information for treating emergency room patients. However, reading discharge summaries may occupy more time than emergency care clinicians can afford. It would be beneficial to present vital information in the reports to them so that they would be able to quickly extract and digest it. There are several possible ways to present the information without changing the structure or content of the report itself. As a prelude to an effective study concerning the efficiency of the various presentation approaches, it is first necessary to know which diagnoses would benefit from past history, and what kind of information is most important to present for each of the diagnoses. In this study, we present a method for elucidating emergency care information needs from clinicians. Analysis of the data obtained from clinicians resulted in generation of a list of important diagnoses and informational categories. For validation, the clinicians were shown sample reports and were asked to highlight critical information. Overall, predicted important items correlated with physicians highlighting (Pearson correlation coefficient of 0.650, significance level 0.01).

Emergency Medicine↗

Cloning, characterization, and the complete 56.8-kilobase DNA sequence of the human NOTCH4 gene.

The first complete mammalian genomic sequence reported thus far in the Notch gene family, including a putative promoter region and 30 exons of the human NOTCH4 gene spanning 56.8 kb of DNA, were sequenced. The NOTCH4 locus contains a TATA-less promoter with two putative transcription initiation sites (Inr), three RBP-Jkappa sites, and two GATA recognition sites. Two cDNA isoforms, NOTCH4(L) and NOTCH4(S),were identified. Whereas the NOTCH4(S) isoform contains the entire coding sequence, the NOTCH4(L) isoform has two unspliced intronic sequences between exons 11 and 12 and exons 20 and 21 and a misspliced exon 6. Consistent with these results, two alternatively spliced isoforms of transcripts of approximately 9.3 and 6.7 kb were detected by Northern blot analysis. The predicted amino acid sequence of the NOTCH4 protein based on the NOTCH4(S) cDNA sequence contains 2003 amino acids and includes the predominant motifs of the Notch family: 29 epidermal growth factor (EGF)-like repeats, 3 Notch/lin-12 repeats, a transmembrane region, 6 cdc10/Ankyrin repeats, and a PEST domain.

Adult↗

Requirements for infrastructure and essential activities of infection control and epidemiology in hospitals: A consensus panel report. Society for Healthcare Epidemiology of America.

The scientific basis for claims of efficacy of nosocomial infection surveillance and control programs was established by the Study on the Efficacy of Nosocomial Infection Control project. Subsequent analyses have demonstrated nosocomial infection prevention and control programs to be not only clinically effective but also cost-effective. Although governmental and professional organizations have developed a wide variety of useful recommendations and guidelines for infection control, and apart from general guidance provided by the Joint Commission on Accreditation of Healthcare Organizations, there are surprisingly few recommendations on infrastructure and essential activities for infection control and epidemiology programs. In April 1996, the Society for Healthcare Epidemiology of America established a consensus panel to develop recommendations for optimal infrastructure and essential activities of infection control and epidemiology programs in hospitals. The following report represents the consensus panel's best assessment of needs for a healthy and effective hospital-based infection control and epidemiology program. The recommendations fall into eight categories: managing critical data and information; setting and recommending policies and procedures; compliance with regulations, guidelines, and accreditation requirements; employee health; direct intervention to prevent transmission of infectious diseases; education and training of healthcare workers; personnel resources; and nonpersonnel resources. The consensus panel used an evidence-based approach and categorized recommendations according to modifications of the scheme developed by the Clinical Affairs Committee of the Infectious Diseases Society of America and the Centers for Disease Control and Prevention's Hospital Infection Control Practices Advisory Committee.

Accreditation↗

A survey of infection control professional staffing patterns at University HealthSystem Consortium institutions.

BACKGROUND: Proper staffing of infection control departments has long been a topic of interest. The most complete report on the subject, the Study on the Efficacy of Nosocomial Infection Control, was published in 1985. To provide current benchmarking comparison data for expected staff reductions at the University of Michigan Health System, a survey of University HealthSystem Consortium members was performed. METHODS: A survey tool was developed to obtain general demographic, staffing, and case-mix information. An infection control professional at each institution was contacted to obtain most of the information. Additional information was obtained from standard references. RESULTS: Responses were obtained from 45 University HealthSystem Consortium members (67%). Full-time equivalent ratios were based on the following parameters and compared for the institutions: number of occupied beds (according to occupancy rate, median 137 occupied beds/full-time equivalent), number of intensive care unit beds (median 28 beds/full-time equivalent), number of admissions or discharges (median 6686 admissions/full-time equivalent), number of ambulatory care visits (median 104,426 visits/full-time equivalent), and case-mix index (median 1.75). CONCLUSIONS: Many institutions are using benchmarking comparison data to make decisions regarding staff reductions. This survey provides preliminary data for determining the "best practice" in staffing for infection control departments. More information may be needed to evaluate other factors that affect infection control professionals' workload.

Academic Medical Centers↗