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Colon cancer poses a significant threat to human life with a high global mortality rate. Early and accurate detection is crucial for improving treatment quality and the survival rate. This paper presents a comprehensive approach to enhance colon cancer detection and classification. The histopathological images are gathered from the CRC‐VAL‐HE‐7K dataset. The images undergo preprocessing to improve quality, followed by augmentation to increase dataset size and enhance model generalization. A deep learning based transformer model is designed for efficient feature extraction and enhancing classification by incorporating a convolutional neural network (CNN). A cross‐transformation model captures long‐range dependencies between regions, and an attention mechanism assigns weights to highlight crucial features. To boost classification accuracy, a Siamese network distinguishes colon cancer tissue classes based on probabilities. Optimization algorithms fine‐tune model parameters, categorizing colon cancer tissues into different classes. The multi‐class classification performance is evaluated in the experimental evaluation, which demonstrates that the proposed model provided highest accuracy rate of 98.84%. In this research article, the proposed method achieved better performance in all analyses by comparing with other existing methods. Research Highlights: Deep learning‐based techniques are proposed.DL methods are used to enhance colon cancer detection and classification.CRC‐VAL‐HE‐7K dataset is utilized to enhance image quality.Hybrid particle swarm optimization (PSO) and dwarf mongoose optimization (DMO) are used.The deep learning models are tuned by implementing the PSO‐DMO algorithm. [ABSTRACT FROM AUTHOR]

The people counting detection is used to detect the object by using a deep neural network. By using this process we can get more accuracy. Before that, we used the k means algorithm. But we can get only less accuracy. So, we can move to the neural network. It gives better accuracy. For the identification, we are taking blob to detections. Used in commercial applications, face identification, object tracking, image retrieval, and automated parking system. In this project, we will dive deeper and look at various algorithms that can be used for object detection. [ABSTRACT FROM AUTHOR]

Background: Thyroid abnormalities are common in chronic heart failure. Severity of heart failure rises by several fold in patients with thyroid dysfunction. Objectives: The purpose of this prospective study is to determine the correlation between low T3 syndrome and chronic heart failure with 2D echocardiography features & predicting the severity of chronic heart failure. Methods: In this descriptive, prospective cross sectional study, all patients who presented to the department of medicine with chronic heart failure during this study period of 12 months from January 2010-December 2011 in K.R.Hospital, Mysore were included. Patients were grouped into Low T3 chronic heart failure, hypothyroid chronic heart failure and chronic heart failure. Results: Mean age of low T3 chronic heart failure patients was higher than other two groups [60.50±6.15(SD) years, Systolic dysfunction on 2D Echo was more in low T3 dilated cardiomyopathy (20%), Diastolic dysfunction on 2D Echo was more in low T3 dilated cardiomyopathy group (30%), Pericardial effusion was seen in more number of patients with low T3 dilated cardiomyopathy (10%).Global hypokinesia was seen in more number of patients with low T3 dilated cardiomyopathy (30%).Segmental hypokinesia was seen in more number of patients with low T3 dilated cardiomyopathy (3%). Mean ejection fraction was seen in more number of patients with low T3 dilated cardiomyopathy [36.78±5.08 (SD)%]. Mean ejection fraction was lower in low T3 dilated cardiomyopathy [34.8±3.293 (SD) %].The high pulmonary artery systolic pressure was seen in more number of patients in low T3 dilated cardiomyopathy (70%).Conclusion: There is significant percentage of chronic heart failure patients having low T3 alone as biochemical parameter. It is important to recognize patients with chronic heart failure as it is associated with increased severity of heart failure. [ABSTRACT FROM AUTHOR]

Although they furnish accurate displacements, conventional displacement-based lower order finite elements fail to predict accurate stress resultants and stresses in certain classes of plate and shell problems that involve free edges, steep stress gradients and singularities. In order to tackle such problems, a triangular higher-order shell element based on the nodal basis approach has been developed. The nodes of the element are located at optimal points and its more superior shape functions derived from orthogonal Proriol polynomials. To illustrate the improved performance of the higher-order element as compared to commonly used lower order shell elements in predicting the variations of stress resultants and stresses, three example problems involving a simply supported skew plate, a corner supported square plate, and a clamped cylindrical shell are solved. The stress resultants and the stresses furnished by the higher-order element for the problems considered are found to be accurate with the satisfaction of the natural boundary conditions and devoid of any oscillations. When compared to lower order elements, the higher-order element requires a simple mesh design and lesser degrees of freedom resulting in a considerable reduction in the computational effort, especially for large scale nonlinear analysis. [ABSTRACT FROM AUTHOR]

Background: Left ventricular (LV) function might be altered in type 2 diabetes (DM) and microalbuminuria (MA) may accentuate the abnormalities. We sought to investigate whether additional LV dysfunction could be unmasked using tissue Doppler (TVE)-enhanced dobutamine stress echocardiography (TVE-DSE) in patients with DM + MA. Methods: Twenty seven DM subjects with MA, (DM + MA), 31 DM subjects without MA (DM - MA), and 13 Controls were evaluated using TVE-DSE. LV basal peak systolic (PSV), early (E') and late (A') diastolic velocities (cm/sec) at rest and peak stress were post-processed. LV filling pressure was assessed using E/E'ratio. Results: PSV and E'velocity at peak stress in the respective three groups were 13.7 +/- 1.0, 10.1 +/- 1.1, 10.0 +/- 1.2 for PSV; and 10.0 +/- 1.6, 5.0 +/- 1.4, 4.8 +/- 1.4 for E' (p < 0.001 for controls vs. both groups). E/E' at rest was 7.9 +/- 0.7 in the controls, 10.8 +/- 2.4 in DM - MA, and 11.0 +/- 2.2 in DM + MA (p < 0.01 Controls vs. both the DM groups). Conclusions: Patients with DM + MA do not have additional LV regional systolic and diastolic dysfunctions compared with DM -MA, as revealed by TVE-DSE, when controlled for glycemia levels, lipids, and treatment strategies. [ABSTRACT FROM AUTHOR]

Background: Although the impact of type 2 diabetes mellitus (DM) and hypertension (HTN) on myocardial function has recently been studied using tissue Doppler echocardiography (TDE), the independent role of both conditions, and the influence of other risk factors on myocardial function has not been completely defined, particularly in absence of coronary artery disease (CAD). The aim of this study was to assess the myocardial functional reserve in patients with DM or HTN with apparently normal left ventricular (LV) systolic function., Methods: Standard and dobutamine stress echocardiography using TDE was performed in 128 subjects: 59 had DM, 20 had HTN, 27 had both DM and HTN (HTN + DM), and 22 subjects were controls (C). Subjects with known CAD and depressed LV function were excluded. In addition, standard two-dimensional and Doppler measurements, LV regional peak systolic (PSV), early (E') and late (A') diastolic velocities, strain (S%) and strain rate (SR), were assessed at rest and peak stress., Results: The LV mass did not differ, although relative wall thickness was significantly higher in subjects with HTN + DM and HTN. The PSV did not differ at rest but was lowest in subjects with HTN + DM at peak stress. The E' wave velocity was significantly lower in subjects with HTN + DM both at rest and during peak stress, as were S% and SR., Conclusions: The addition of DM to HTN has a negative effect on LV systolic and diastolic functions. A depressed myocardial functional reserve might be postulated as one of the pathophysiologic mechanisms for the excessive occurrence of congestive heart failure in patients with DM or HTN.

Background: Streptokinase is the most widely used thrombolytic agent and can now be made using recombinant DNA technology. The present trial was initiated to assess an indigenous recombinant streptokinase (Shankinase, r-SK)., Aim: To compare the efficacy and safety of indigenous recombinant streptokinase (Shankinase, r-SK) and natural streptokinase (Streptase, n-SK)., Settings and Design: Double blind, randomized, non-inferiority, multicentric, parallel study., Materials and Methods: Patients of AMI < 6 hours of chest pain and 2 mm ST elevation in 2 contiguous chest leads V(1)-V(6) or 1 mm in limb leads were randomized to receive 1.5 miu of either r-SK or n-SK. CK Peaking and decrease of > or = 50% ST segment were used to assess reperfusion., Statistical Analysis: Difference in the groups was assessed by chi-square or paired t test as required. Probability value < 0.05 was considered significant with 95% confidence interval., Results: Overall 150 patients were recruited (96 r-SK group and 54 in n-SK group) and demographic and clinical profile of the groups was comparable. Reperfusion was seen in 68.2% (58) and 69.4% (34) patients in r-SK and n-SK groups respectively. Commonly seen adverse events were fever in 7 (8.5%), hypotension in 3 (3.6%), nausea in 2 (2.4%) patients. Minor bleeding were seen in 4 (4.8%) of patients., Conclusion: Indigenous recombinant Streptokinase (r-SK) is as efficacious as natural streptokinase (n-SK) in establishing reperfusion as assessed by non-invasive parameters with comparable side effect profile.