9/5/2023 0 Comments Graphpad prism heatmap![]() ![]() We found that the structure of ECG data is similar to the structure of genome sequencing data. In all, a heat map conveys complex data concisely and completely at a single glance.Īt present, heat maps are mainly used to display genome sequencing results. Moreover, individual data points can be grouped together based on their corresponding heat map color. By virtue of the inherent sensitivity of human beings to color, heat maps transform data into a color summary, which makes the distribution and characteristics of the data clear at a glance and makes it easy to distinguish and summarize abnormalities. Different colors are used to represent the magnitude of a certain monitoring value. Ī heat map is a graphical representation of data that simultaneously reveals the row and column hierarchical cluster structure in a data matrix. Moreover, traditional charts cannot show data intuitively, which is not conducive to a synthesized understanding of the results. Traditional charts have difficulty fully showing the details of each case, and only briefly quantify the proportion of target changes and the average value of the changes. Nevertheless, for the moment, most clinical ECG studies still take advantage of traditional statistical functions, and their results are mostly presented by traditional charts, such as tables, histograms, and curves. Therefore, in clinical research, it would be helpful for readers to analyze, understand and memorize the data and research conclusion by showing the individual ECG results for each lead. An electrocardiogram (ECG) contains multiple lead data, and the combinations of different ECG lead shifts have different clinical significance. Heat maps and cluster analysis can be used to fully display every lead of each electrocardiogram and provide relatively comprehensive information.Įlectrocardiography, a non-invasive and economical detection method, is widely used in clinical practice. Cluster analysis in the heat map showed that the III, aVF and aVR leads could be clustered together, the V 1, V 2, V 3 and V 4 leads could be clustered together, and the V 5, V 6, I and aVL leads could be clustered together. These cases also could be fully displayed and visualized in the heat map. Moreover, the STE amplitude in 40% (24 out of 60) of cases reached the threshold specified in the STEMI guideline. According to cluster analysis in the heat map, STE leads were clustered into two categories, comprising of the right precordial leads (V 1, V 2, V 3) and others (V 4, V 5, V 6, I, II, III, aVF, aVL, aVR). The ST-segment shifts of each lead of each collected ECG could be conveniently visualized in the heat map. ![]() ![]() STE leads were mainly in the V 1, V 2 and V 3 leads. In total, 60 cases of electrocardiographic LVH with STE were screened and analyzed. Cluster analysis was carried out based on the heat map and the results were drawn as tree maps (pedigree maps) in the heat map. HemI 1.0 software was used to draw heat maps to display the STE of each lead of each collected ECG. We sequentially collected the electrocardiograms of inpatients in the First Affiliated Hospital of Shantou University Medical College from July 2015 to December 2015 in order to screen cases of LVH with STE. The aim of this study was to analyze and show data for electrocardiographic left ventricular hypertrophy (LVH) with ST-segment elevation (STE) by a heat map in order to explore the feasibility and clinical value of heat mapping for ECG data visualization. Few papers display ECG data by visual means. Most electrocardiogram (ECG) studies still take advantage of traditional statistical functions, and the results are mostly presented in tables, histograms, and curves. ![]()
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