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At least 1,279 records · Page 71Linked to original sources
PubMed2002

Using machine vision to analyze and classify Caenorhabditis elegans behavioral phenotypes quantitatively.

Mutants with abnormal patterns of locomotion, also known as uncoordinated (Unc) mutants, have facilitated the genetic dissection of many important aspects of nervous system function and development in the nematode Caenorhabditis elegans. Although a large number of distinct classes of Unc mutants can be distinguished by an experienced observer, precise quantitative definitions of these classes have not been available. Here we describe a new approach for using automatically-acquired image data to quantify the locomotion patterns of wild-type and mutant worms. We designed an automated tracking and imaging system capable of following an individual animal for long time periods and saving a time-coded series of digital images representing its motion and body posture over the course of the recording. We have also devised methods for measuring specific features from these image data that can be used by the classification and regression tree classification algorithm to reliably identify the behavioral patterns of specific mutant types. Ultimately, these tools should make it possible to evaluate with quantitative precision the behavioral phenotypes of novel mutants, gene knockout lines, or pharmacological treatments.

Algorithms↗
PubMed2003

How to minimize inappropriate utilization of Accident and Emergency Departments: improve the validity of classifying the general practice cases amongst the A&E attendees.

Studies have found that one-third to two-thirds of all patients attending Accident and Emergency (A and E) Departments could be managed appropriately by general practitioners (GPs). There is also evidence that referral to GPs can be acceptable to patients. The question of primary concern is screening non-urgent cases with high degrees of sensitivity (S), specificity (SP), and positive predictive value (PPV). This paper reports the findings of the validity (S, SP and PPV) of nurses and patients in triaging A and E visitors. A cross sectional study was conducted over a 1 year period and subjects were randomly selected from four A and E Departments located across the four principle geographic regions of Hong Kong by stratified, two-stage sampling. S, SP and PPVs were computed for both non-weighted and weighted conditions. The gold standard for defining the true urgency status of each selected patient was based on a review of the patient's record 3-21 days (or longer if necessary) following the A and E visit. The record review in each A and E was blinded and done independently by a panel of two (and if disagreement existed, three) senior emergency physicians who did not practice in the same hospital. The greatest weights would be for incorrect decisions with greatest impact on patients' well being. The most accurate unweighted nurses' triage classification had an average sensitivity of 87.8%, specificity of 83.9%, and a PPV of 70.1%. When weighted, the average sensitivity reduced to 75%, specificity to 65.7%, and PPV to 54%. The most accurate unweighted patients' self-triage classification yielded a sensitivity of 62.5%, specificity of 69.2%, and a PPV of 58.1%, and correspondingly reduced to 43.3, 49.2 and 38.6% if weights were applied. Validity of the derived patients' self-classifications was too inaccurate for practical use. Hong Kong's current use of a five-point urgency scale by nurses would be further refined for identifying non-urgent visitors. If a mechanism was put in place for additional screening on visitors with a borderline semi-urgent or non-urgent status, the nurses could safely reassign non-urgent patients to GP care. If implemented, a significant impact on hospital costs could be realized.

Concurrent Review↗
PubMed1989

The failure of prehospital trauma prediction rules to classify trauma patients accurately.

Clinical prediction rules are used extensively by most regionalized trauma systems to identify which patients have sustained major injuries. Because of reported high misclassification rates of some of these rules and the known global difficulty of transporting prediction rules, four such rules (the Trauma Score, the CRAMS Scale, the Revised Trauma Score, and the Prehospital Index) and two newly derived rules were statistically analyzed using a cohort of 2,434 injured patients. All rules accurately predicted mortality with a minimum sensitivity and specificity of 85%. However, not one of the rules was able accurately to identify surviving patients who had sustained major injuries. In this instance, no rule was able to achieve a sensitivity of at least 70% while achieving a specificity of 70%. These results suggest that the problem with trauma prediction rules lies in the inherent limitations of the clinical data on which they are based. In view of this, the usefulness of existing prehospital trauma predictive rules must be questioned.

Adult↗
PubMedDate not supplied

Significance of keratosis and dyskeratosis for classifying hyperplastic aberrations of laryngeal mucosa.

Retrospective study of 325 tissue samples of hyperplastic aberrations of the laryngeal mucosa by means of light and electron microscopy and immunohistochemical methods has demonstrated that superficial keratinization is not important for determining changes into precancerosis or "risky epithelium" or even for the progress from hyperplastic aberrations to carcinoma. The degree of keratinization of the epithelial surface in all three forms of hyperplastic aberrations is almost the same. In grouping the hyperplastic aberrations into "precanceroses" or "risky epithelium," the following morphologic changes have to be considered as extremely important factors: the occurrence of dyskeratotic cells, the basalification of the epithelium, and the response of the organism in the form of infiltration of immunocompetent cells in the subepithelial stroma.

Adult↗
PubMedDate not supplied

Classified care.

Explore the source record for details and available documents.

Activities of Daily Living↗
PubMedDate not supplied

MRI of the hippocampus in Alzheimer's disease: sensitivity, specificity, and analysis of the incorrectly classified subjects.

In this study, magnetic resonance imaging (MRI) of the hippocampus for the diagnosis of early Alzheimer's disease (AD) is evaluated. We measured hippocampal volumes and the area of the medial hippocampus with a 1.5 T MR imager in 160 subjects: 55 patients with probable AD according to the NINCDS-ADRDA criteria, 43 subjects fulfilling the NIMH criteria of age-associated memory impairment (AAMI), 42 cognitively normal elderly controls, and 20 controls younger than 50 years. Three methods for normalization were compared. The hippocampi were atrophied in the AD patients, but not in the AAMI subjects or the elderly controls. There was no significant correlation between hippocampal volumes and age in the nondemented subjects. The discrimination based on volumetry resulted in an overall correct classification of 92% of AD patients vs. nondemented elderly subjects, whereas discrimination based on hippocampal area was less accurate, producing a correct classification in 80% of the subjects. We conclude that the hippocampus as assessed by MRI volumetry is atrophied early in AD, and spared by aging or AAMI. A brief critical review of previous studies is in concordance with the presented data: all the previous studies that have used volumetry, have similarly ended up with a good classification, whereas simpler or subjective measurements, subject to various sources of bias, have produced most variable results.

Aged↗