Title: Smart health care technologies to support computer aided diagnostics

Abstract

Cardiovascular diseases (CVD): Now a day’s number one cause of death. The mortality rate due to CVD is around 272 person per lakh in comparison to 235 per person globally.ECG is commonly used signal to detect it for initial findings. Several approaches based on wavelet-based variants on ECG are studied to detect coronary artery diseases and helping the computer aided diagnostic system. Apart from ECG, EEG test is very much popular to detect any brain activity disorder. EEG signals are also used in Brain-computer interfaces (BCIs). Detecting early any diseases or any brain disorder may help us to save lives of several people who commits suicide (eg. Farmers). In this talk, major discussion will be based on how Deep learning-based approaches can be used to improve the diagnosis task. The task primarily consists of two sub problems. First part of the discussion will be focused on identification of abnormal cases, i.e., whether the brain contains any symptoms or not. In the second part classification of the type will be discussed in details. Automatically categorizing the diseases type is a relatively more challenging task comparing to the binary classification of normal and abnormal personal and convolutional neural networks are found to be very successful in biological tasks.