Computational Analysis and Deep Learning for Medical Care

15Deep Learning for Medical Healthcare: Issues, Challenges, and Opportunities

Meenu Gupta^1*, Akash Gupta^2† and Gaganjot Kaury^1‡

¹Chandigarh University, Punjab, India

²Bharati Vidyapeeth’s College of Engineering, New Delhi, India

Abstract

Human beings are facing lots of problems related to health issues due to carelessness. Medicines are one of the powerful tools for the medical care system. But, identifying the best medicine is still an issue for a particular disease. Advance medical technology has resolved the issue of the healthcare problem. Bio-medical remains a key challenge in healthcare-related issues. Modern biomedical research collected data from e-health records, medical imaging, sensor, and text data which are complicated and not in structure. Only collecting data is not the solution to solving the health-related issue. This data enhances the learning about health of human and common diseases. Deep learning (DL) is a fast-growing field of machine learning which helps to manage a large amount of data. Presently, we stand at the origination of revolution in medical healthcare. Mostly, medication is still depending upon the symptoms and trial remedies in spite of all available scientific knowledge; it is not suitable to all patients but few of them gets relief, minimizes difficulties, and makes better chance of survival. It is crucial to understand the relationship between diseases to bring new perceptions into taxonomy of diseases. This chapter mainly focuses on issues ...