The Role of Machine Learning and Deep Learning Approaches in the field of HealthCare

Abstract

Healthcare and medical science are the most happening area in the last few decades. There are lot many technological innovations carried out in this field as per the need of the current era. Healthcare has gained a prominent place in human lives. Predictive and analysis tools are urgently needed as a result of the development of technology in health care and medical sciences, which produce vast amounts of data that are beyond the capacity of humans. Their findings will open up a variety of research opportunities while also fostering improved judgments and decision-making in medical and healthcare companies. This leads to addressing the prominent use of advanced technologies namely, artificial intelligence and its subsets which imitate human intellect, evaluate data, and produce truthful outcomes. One of them is machine learning, which uses predetermined computer learning patterns for a certain dataset to achieve novel outcomes with previously undiscovered data.

As machines learn how to optimize themselves to deliver amazing results, this requires the least amount of human interaction. However, it is not without flaws, as these algorithms cannot learn deep patterns and do not learn with accuracy. To address these issues, deep learning algorithms have been developed. There are numerous layers or levels of abstraction in a deep learning environment, which aids in identifying the intricacy of the patterns hidden in the data. This paper is constructed with the goal to scrutinize the place of ML and DL in the healthcare and medical industries. Also, it provides an overview of medical imaging in the machine and deep learning techniques used for analyzing different diseases.