Applications of Deep Learning in Medical Engineering

As a result of considerable breakthroughs in the field of artificial intelligence, deep learning has achieved exceptional success in resolving issues.This work brings forth a historical overview of deep learning and neural networks and further discusses its applications in the domain of medical engineerings - such as detection of brain tumours, sleep apnea, arrhythmia detection, etc. One of the most important and mysterious organs of our body is the brain. Like any other organ, our brain may suffer from various life-threatening diseases like brain tumours which can be malignant or benign. Analysis of the brain MRI images by applying convolution neural networks or artificial neural networks can automate this process by classifying these images into various types of tumours. A faster and more effective method can be provided by this method for detecting the disease at a key stage from where recovery is possible. Sleep apnea is a sleeping disorder involving irregular breathing. The brain detects a sudden decrease in the level of oxygen and sends a signal to wake the person up while he is sleeping. Cardiac arrhythmia refers to a group of conditions that causes the heart to beat irregularly, too slowly, or too quickly, e.g., atrial fibrillation. Deep learning along with bio-medical signal and audio processing techniques on respiratory sound datasets and ECG datasets have huge potential in the detection of these diseases. Deep learning outperforms the existing detection algorithms and a good amount of effort on feature engineering, augmentation techniques, and building effective filters can get a high accuracy result.

Keywords: Artificial intelligence, Artificial neural networks, Atrial fibrillation, Automation, Audio processing, Brain tumours, Bio-medical signal processing, Cardiac arrythmia, Convolution neural networks, Deep learning, ECG, EEG, Feature engineering, Machine learning, MRI imaging, Neural networks, Optimization, Signal processing, Signal analysis, Sleep apnea.