Deep Learning for Medical Healthcare: Issues, Challenges, and Opportunities
Meenu Gupta, Akash Gupta, Gaganjot Kaur · 2021
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 and challenges that occur in medical healthcare. Further, this chapter also discussed some medical health issues problem such as cancer, tumor, breast cancer, Alzheimer, and many more diseases with the role of DL.