Distribution of information in biomedical abstracts and full-text publications.

MOTIVATION: Full-text documents potentially hold more information than their abstracts, but require more resources for processing. We investigated the added value of full text over abstracts in terms of information content and occurrences of gene symbol--gene name combinations that can resolve gene-symbol ambiguity. RESULTS: We analyzed a set of 3902 biomedical full-text articles. Different keyword measures indicate that information density is highest in abstracts, but that the information coverage in full texts is much greater than in abstracts. Analysis of five different standard sections of articles shows that the highest information coverage is located in the results section. Still, 30-40% of the information mentioned in each section is unique to that section. Only 30% of the gene symbols in the abstract are accompanied by their corresponding names, and a further 8% of the gene names are found in the full text. In the full text, only 18% of the gene symbols are accompanied by their gene names.

Employment of intra-individual variability to improve computerized ECG interpretation.

One of the reasons for the limited practical utility of computer programs for interpretation of electrocardiograms (ECGs) is their susceptibility to intra-individual variability. Two of the most prominent sources of intra-individual variability in ECGs, electrode placement variations and respiration, were studied for their effects on computerized ECG interpretation. Previous research has shown that the effects of intra-individual variability on computerized ECG interpretation depend largely on the individual ECG. To enable the assessment of chest electrode position variations for individual standard 12- lead ECGs, ECGs resulting from simulations of such position variations were interpreted. Variability due to respiration was assessed by interpreting all individual ECG beats instead of an averaged beat. In this paper two methods are presented that employ information about the intra-individual variability in individual ECGs. The first method provides an estimate of the reliability of the interpretation, the second attempts to improve the interpretation itself. In the first method we quantified the variation in interpretation caused by the two sources of intra-individual variability with the use of a stability index, a high index value indicating a low variation in interpretation. This index was subsequently studied using two sets of ECGs. For the first set a â clinical' reference interpretation was obtained from discharge letters. For the second set three cardiologists provided a â cardiologists' reference. The performance of subgroups of ECGs having stability indices higher than a particular value was computed. It appeared that for the â cardiologists' reference, the interpretations of ECGs with a high stability index were more often correct. No effect was found for the â clinical' reference. In the second method we attempted to improve the original interpretation by combining the alternative interpretations into a new interpretation. This was done by taking the median or the average of the quantified alternatives. These combined interpretations proved to perform better than the original interpretation when a cardiologist's interpretation was taken as a reference. This paper shows that intra-individual ECG variability can be used to improve original interpretations. This can be done without having to record multiple ECGs, provided that a model is available to simulate intra-individual variability. The presented methods do not depend on the classification algorithm that is used. They can be used both during classifier design to correct imperfections, and in routine use of the classifier to produce more representative classifications.

Effect of electrode positioning on ECG interpretation by computer.

The aim of this study was to assess the variability in automated electrocardiogram (ECG) interpretation due to electrode positioning variations. Such variations were simulated by using a set of 746 body surface potential mappings from apparently healthy individuals and patients with myocardial infarction or left ventricular hypertrophy. Four types of electrode position changes were simulated, and the effect on ECG measurements and diagnostic classifications was determined by a computer program. At most 6% of the cases showed important changes in classification for longitudinal shifts. Transversal shifts causes less than 1.5% of important changes. An expert cardiologist, who analyzed a subset of 80 cases, agreed with the computer in 38 of 40 cases in which it made no change. In the 40 cases with large diagnostic changes, the cardiologist made no change in 18 cases. The effect of electrode position changes on ECG classification by an expert cardiologist was about half of the effect determined by computerized ECG classification. The effects on classification are significant; therefore, correct placement of chest electrodes remains mandatory.

Interpolation of body surface potential maps.

The performance of four methods for interpolation of body surface potential maps (BSPMs) for different electrode grid densities was assessed. This study is part of a research project on the influence of the variability of 12-lead electrocardiograms on computer interpretation due to small electrode position changes. Interpolated BSPMs can be used to simulate this variability. The set of BSPMs studied, derived from a 117-electrode grid with relatively many electrodes on the left precordial part of the thorax, consisted of 232 cases without abnormalities, 277 with infarction, and 237 with left ventricular hypertrophy. The interpolation methods used were fast Fourier transforms, Chebyshev polynomials, linear functions, and cubic splines (CS). In the horizontal plane, a reference signal was first interpolated and, thereafter, resampled using 11 different sets of electrodes with the number of electrodes ranging from 18 down to 8. In the vertical direction, five grids with electrodes only on the front of the thorax and nine grids with electrodes on the front and back were examined. As a performance measure for interpolation, mean absolute error (MAE) was used: the absolute differences between the reference signal and the interpolated signal, averaged over the QRS on all maps. All methods showed deteriorating performance for decreasing grid density. In the horizontal direction, CS proved to be slightly superior to other methods for the left precordial electrodes for all but the densest grid (e.g., MAE = 22.8 microV vs MAE > 24.8 microV for a 12-electrode grid). For electrodes not in that area, CS performed the best as well (MAE = 16.1 microV for the same grid), with differences with the other methods being small (MAE > 16.4 microV). In the vertical direction, CS showed the best results on the front, both for the dense nonperiodic (MAE = 19.1 microV vs MAE > 26.6 microV for a 6-electrode grid) and periodic grids (MAE = 25.1 microV vs MAE > 26.6 microV for a 12-electrode grid). Linear functions performed best for sparse nonperiodic grids and sparse periodic grids for electrodes on the back, with the difference with CS for the last case being small. The method CS performed best overall, and is recommended for interpolating BSPMs.