# A Brief Review on Gender Identification with Electrocardiography Data
## 3 Results
Non-Hodgkin's lymphoma diagnoses were associated with a higher frequency of CA (17/31; 54.8%) compared to a lower frequency of CA (7/106; 6.6%) and a QTc > 500 milliseconds at any point during transplantation (8/31; 25.8%) compared to a QTc < 500 (6/106; 5.6%) (\(p\) = 0.0011). The authors of [22] used the ECG parameters of the right bundle branch block (RBBB) and Si(QIII)-type patterns to investigate the ECG parameter changes for risk stratification in acute pulmonary embolism (PE). The experiments were performed on patients with a confirmed diagnosis of acute PE treated at the Internal Medicine Department between May 2006 and June 2011. The analyses were performed by 175 patients treated at the Internal Medicine Department and were included in this retrospective analysis. The research sample included 138 PE patients (78.9%) without both symptoms and 37 PE patients (21.1%) with RBBB and Si(QIII)-type patterns. Heart rate (97.4 \(\pm\) 17.2 vs. 93.2 \(\pm\) 26.8/min, \(p\) = 0.021), cardiac troponin I levels (0.19 \(\pm\) 0.38 vs. 0.11 \(\pm\) 0.24, \(p\) = 0.003), and the ratio of patients with RVD (83.9% vs. 52.7%, \(p\) = 0.005) were all substantially greater in PE patients with RBBB and Si(QIII)-type pattern alterations. Significant correlations between RBBB and RVD were found with multivariate logistic regression models adjusted for age and gender (OR 3.942; 95 percent CI 1.054-14.747; \(p\) = 0.042) and between Si(QIII)-type patterns and RVD (OR 5.667; 95 percent CI 1.144-28.071; \(p\) = 0.034). While the correlation between Si(QIII)-type patterns and cardiac damage was significant (OR 3.956; 95 percent CI 1.309-11.947; \(p\) = 0.015), the correlation between RBBB and cardiac injury (cTnI N 0.4 ng/mL) revealed a borderline significance (OR 2.531; 95 percent CI 0.973-6.583; \(p\) = 0.06). In [17], the author compared two-dimensional representations of ECG in three different approaches. The emphasis was placed on maintaining stable conditions to determine the features and validate the proposed methods. The participants had atrial fibrillation, and the results obtained for the spectrogram and scalogram were similar and confirmed the effectiveness of the processes in detecting atrial fibrillation. Attractor reconstruction was inferior to the other two but still effective. [PERSON] et al. [25] analyzed data with concentration cut-points, ECG findings, logistic regression (LR), and classification and regression tree (CART) analysis. Within 48 h of the commencement of their chest symptoms, 92 patients with acute myocardial infarction underwent the examinations, along with 105 asymptomatic healthy controls. In addition, they repeated the CART analysis on 58 cases and 58 controls, ones that were matched for age and gender, allowing for a sensitivity analysis to be carried out. As evaluated by LRand CART, this investigation showed that serum biomarkers had higher acute myocardial infarction sensitivity and specificity than saliva. The authors of [21] used ECG and echocardiogram (ECO) in patients with acute myocardial infarction from the China Acute Myocardial Infarction (AMI) registry from January 2013 to September 2014 to develop a risk model to predict in-hospital death among contemporary AMI patients as soon as possible after admission; 541 (9.3%) individuals with NSTEMI who had an early invasive approach did so. Among the patients with STEMI, 1739 (9.9%) received thrombol treatment, whereas 7587 (43.2%) patients had primary PCI. In [24], the authors used a 12-lead electrocardiography in 2232 healthy community-based participants without known cardiac disease aged 70+ in rural Tanzania. Digital electrocardiograms were analyzed, and after univariate analysis of the covariance using a multiple linear regression model, adjusting for age; systolic blood pressure (SBP); body mass index (BMI); RR interval; gender-specific reference values for the P duration (PD), P amplitude (PAMP), P area (PAREA), P terminal negative force (V1) (PTNF), PR interval, QRS duration (QRSD), and QT/QTc.