Pulmonary artery thromboendarterectomy (PTE) has been regarded as a promising, potentially curative surgical procedure. However, PTE is associated with specific postoperative complications, such as reperfusion pulmonary edema and right heart failure leading to a considerable mortality of 7-24%. Despite its limitations PTE is a better surgical alternative to lung transplantation which carries high morbidity and mortality. The aim of the study is to analyze the efficacy, safety, morbidity and survival associated in the postoperative period and quality of life after six months of PTE in Indian patients. Forty-one patients with surgically correctable chronic thromboembolic pulmonary hypertension underwent pulmonary endarterectomy. All patients were in New York Heart Association (NYHA) Class II, III or IV. Preoperative mean pulmonary artery pressure was 40.98 +/- 9.29 mmHg and mean pulmonary vascular resistance was 418.39 +/- 95.88 dynes/sec/cm(-5). All patients were followed up to six months and a telephonic survey was conducted using a standard questionnaire. They were assessed and classified as per NYHA grading. There was a significant reduction in the mean pulmonary artery pressure (from 40.98 +/- 9.29 mmHg to 24.13 +/- 7.36 mmHg, P < 0.001) and pulmonary vascular resistance (from 418.39 +/- 95.88 dynes/sec/cm(-5) to 142.45 +/- 36.27 dynes/sec/cm(-5), P < 0.001) with a concomitant increase in the cardiac index (from 1.99 +/- 0.20 L/min/m 2 to 3.28 +/- 0.56 L/min/m 2 , P < 0.001) during the postoperative period. The mortality rate in our study was 12.19% (five patients). Ninety per cent of the patients reported a significant improvement in the quality of life and exercise tolerance after surgery compared to the preoperative state. Pulmonary endarterectomy is an effective and potentially curative surgical treatment for patients with severe chronic thromboembolic pulmonary hypertension. The current techniques of operation make the procedure relatively safe and long-term survival, NYHA functional status and exercise capacity improve significantly.
In this work, deep learning methods are used to classify the facial images. ORL Database is used for the purpose of training the models and for testing. Three kinds of models are developed and their performances are measured. Convolutional Neural Networks (CNN), Convolutional Neural Network Based Inception Model with single training image per class (CNN-INC) and Convolutional Neural Network Based Inception Model with several training images per class (CNN-INC-MEAN) are developed. The ORL database has ten facial images for each person. Five images are used for training purpose and remaining 5 images are used for testing. The five images for the training are chosen randomly so that two sets of training and testing data is generated. The models are trained and tested on the two sets that are drawn from the same population. The results are presented for accuracy of face recognition
As the technology is enhancing, people are coming closer to digital life and digital communication. There are many ways to communicate with others through internet in this new advanced era. Most of them are choosing the easiest way of communication i.e., Electronic mail (E-mail). E-mail is the technology that enables user to contact with others by sending mails and also helps in business world communication. There are people who cannot use these technologies because either they are illiterate or do not have ability to see the screen. So, to make this technology closer to visually challenged people, authors proposed a Voice Based E -mail System. This system provides them the facility of communication and makes them much stronger and independent. This architecture will help blind people to access email and other multimedia functions. Leaving behind the old techniques, this voice -based email system will be containing new technologies that will be easily acceptable by visually challenged people.
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