Artificial Intelligence in Health Care System

We at SGT University working on the development of predictive models using feed-forward and backpropagation - Artificial Neural Networks.

Artificial intelligence (AI) offers high precision technology solutions for the diagnosis, prediction of severity, and treatment options of a disease. AI has brought a paradigm shift to the healthcare system, driven by the increasing availability of medical data, and rapid progress of machine learning techniques such as Artificial Neural Networks (ANN) and Deep Learning. In healthcare, AI is being used to mimic the human cognitive function in the field such as psychology, neuroscience, cognitive science, speech, and facial recognition. A major area that uses AI techniques includes cancer, neurology, endocrine, nutritional, and cardiology.

Read Also: Artificial intelligence – Future of Education Through a New Spectrum

AI is an area of computer science that aims to create intelligent machines that work and react like humans. It comprises the design of “intelligent systems” that receive the relevant information from the source and takes actions to maximize the chances of success.AI-assisted system works in three steps which include i. receiving information as “input data”; ii. data processing using a machine learning algorithm; and iii. “output information” which is then used in decision making and action. The success of an AI system solely depends upon the authenticity of the input data i.e. the information, and the applied machine learning protocol to develop AI system. Here, AI has been employed in several ways to extract the most coherent information that can be used as an identifier for diagnosis and for analyzing disease severity. The researchers are focusing on the development of a new learning algorithm that can handle a large volume of information and provide precise output information in a reasonable time frame.

Read Also: Role of Artificial Intelligence In The Area of HR

We at SGT University working on the development of predictive models using feed-forward and back propagation-Artificial Neural Networks. It is being used to predict the pharmacological activity of new chemical entities and nanomaterials. In addition, it is also applied in the toxicity profiling of new substances.

Dr. Manish Kumar Gupta
Professor
SGT College of Pharmacy
SGT University Gurugram

We're here to help you shape the future.