No abstract

Alzheimer is an irreversible neurological disorder. It impairs the memory and thinking ability of a person. Its symptoms are not known at an early stage due to which a person is deprived of receiving medication at an early stage. Dementia, a general form of Alzheimer, is difficult to diagnose and hence a proper system for detection of Alzheimer is needed. Various studies have been done for accurate classification of patients with or without Alzheimer’s disease (AD). However, accuracy of prediction is still a challenge depending on the type of data used for diagnosis. Timely identification of true positives and false negatives are critical to the diagnosis. This work focuses on extraction of optimal features using nature-inspired algorithms to enhance the accuracy of classification models. This work proposes two hybrid nature-inspired algorithms — particle swarm optimization with genetic algorithm (PSO_GA) and whale optimization algorithm with genetic algorithm, (WOA_GA) to improve prediction accuracy. The performance of proposed algorithms is evaluated with respect to various existing algorithms on the basis of accuracy and time taken. Experimental results depict that there is trade-off in time and accuracy. Results revealed that the best accuracy is achieved by PSO_GA while it takes higher time than WOA and WOA_GA. Overall WOA_GA gives better performance accuracy when compared to a majority of the compared algorithms using support vector machine (SVM) and AdaSVM classifiers.

Reports of chronic constrictive pericarditis presenting with hepatomegaly, cirrhosis and ascites but no cardiac symptoms are rare. A 10 year old child presented with refractory ascites and firm hepatomegaly of 2 years duration which partially responded to diuretics. Doppler study showed dilated hepatic veins and inferior vena cava and ruled out hepatic venous outflow tract obstruction. Chest X ray showed pericardial calcification and 2D Echo was suggestive of chronic constrictive pericarditis. A diagnosis of chronic calcified constrictive pericarditis with cirrhosis and refractory ascites was made. Based on previous series which showed that tuberculosis is the most common cause of constrictive pericarditis, tuberculosis as the cause of constrictive pericarditis was kept. Anti tuberculous treatment as per Revised National Tuberculosis Control Program guidelines was started along with oral steroids and diuretics. Child showed response to the treatment and was later referred to cardiac surgery department for further management (pericardectomy).