Page 205 - Handbook of Deep Learning in Biomedical Engineering Techniques and Applications

Chapter 7 Early detection and diagnosis using deep learning 195

research to production and application. There is a requirement of
technological infrastructure that is sufficiently updated to
address this operationality issue.
4. Security
While DL holds exciting opportunities in cybersecurity, it also
poses several security concerns. Considering how susceptible the
output is to a slight change in the input, DL technology can be
easily misused if sufficient security measures are not in place.
Furthermore, informational integrity and security of the AI plat-
form must be considered to enhance security.

1.2 Introduction to biomedical engineering
Biomedical engineering is the application of engineering in
healthcare and biology. While its history dates back to the discov-
ery of a Mummy in Thebes, it has come a long way since then.
Bioengineers regularly work with health professionals such as
doctors and psychiatrists to arrive at medical breakthroughs
that aid humanity. They aim to expand our knowledge upon
the workings of the human body and brain. Aspects of computer
engineering, electrical engineering, natural sciences, and maths
are integrated to arrive at biomedical engineering. Advancements
in the field have led to the development of lifesaving technologies
such as prosthetics and surgical devices (Figs. 7.2 and 7.3).

Visual
Recognition

Natural
Fraud News Language
Detection Applications Processing
of
Deep Learning

Automatic
Machine Self Driving
Cars
Translation

Figure 7.2 Applications of deep learning.