Introducing deep learning in medical domain

Abstract

The buzz words for today, namely artificial intelligence (AI), machine learning (ML), and deep learning (DL), are slowly entering the medical industry over the past decade, which brings technologies and solutions to a change in the structure of the medical field. These technologies are connected, and each one offers something different in the medical field by showing a difference in how medical professionals treat the patient. DL provides the power to transform and deliver a more decadent layer of medical technology solutions. It is progressively available with innovative technologies that have broad applications in the natural world medical field. DL plays a vital role in providing insight to medical professionals, which helps identify diseases at an early stage, thus delivering better tailored and most effective patient care. DL has become a well-known initiative that everyone has an idea about. The AI-DL industry has been developing quickly, which provides some sufficient development opportunities to the medical industry to bring a significant change. According to Gartner, almost 37% of all sectors surveyed use DL in their profession. It has been foreseen that by 2022, around 80% of modern developments will use AI and DL. It has been observed that the year 2021 would bring the most powerful deep understanding and AI trends that might reshape the country's economic, social, and medical domains.This chapter describes DL, the history of deep knowledge in the medical field, the barriers to deep understanding, and DL opportunities in the medical industry. It also focuses on the various methods or algorithms of DL such as convolutional neural network, deep autoencoder, deep Boltzmann machine, deep belief network in biological systems, medical imaging, and health record and report management. It also discusses the various applications of DL in healthcare and how deep understanding is used in medical image analysis.

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