Detecting rosacea skin disease severity level from selfie images with help of Transferee Learning Regression

Abstract

The aspect of detecting and preventing or avoiding a disease is a significant aspect of the health care industry when taking into consideration the behavioral protection that is needed against diseases and pandemics. Presently, due to the prevailing pandemic situation, the healthcare industry is being over-whelmed and facing a large and unmanageable workload when considering the anomaly detection pertaining to the patients. When healthcare workers, researchers and advocates do not possess the in-depth knowledge needed pertaining to a disease as well as its anomaly symptoms, it is a challenging task to identify reluctant individuals. In most of the situations, an average individual will not be able to determine the symptoms of the disease by simply glancing or looking at the facial features. Furthermore, it is difficult to identify dermatological changes that cannot be recognized from a general clinical observation. This influences the need for an accurate, effective and efficient automation pertaining to detection of anomaly and symptoms by simply observing the surface of the face to evaluate diseases such as rosacea, acne, shingles, Covid-19 rashes etc. that portray similar face diseases. Rosacea is identified as a skin disease that is able to affect an individual in the long-term pertaining to the skin surface of the face. Its symptoms are pimples on the skin, redness, swelling as well as superficial dilated blood vessels that is found around the face, nose and neck. Rosacea is identified to be one of the most severe yet common skin conditions or disorders across the globe. Due to its severity, most of the time the tests as well as assessments are conducted by trained and specialized dermatologists in a special and controlled environment. The disease is seen to be mostly spread around the European region since the skin of European citizens are quite sensitive. The real reason behind the disease is unknown. The symptoms can be shown at unexpected instances as well. The need to detect the symptoms of rosacea can be frequent. Therefore, there is a dire need of a certain media to detect the symptoms of the condition with ease and accuracy. Considering the proposed topic, the ultimate goal of the thesis is to develop a mobile application that is able to observe a selfie image at any given time and receive the feedback from the app with regard to the skin condition, the severity as well as preventative measures or remedies pertaining to the skin condition, similar to how a trained and professional dermatologist would.