Page 134 - Handbook of Deep Learning in Biomedical Engineering Techniques and Applications

5

Depression discovery in cancer

communities using deep

learning

1
1
Srishti Sharma, Vaishali Kalra, Rashmi Agrawal 2
1 2
The NorthCap University, Gurugram, Haryana, India; Manav Rachna
International Institute of Research and Studies (MRIIRS), Faridabad, Haryana,
India

1. Introduction

According to the World Health Organization, cancer refers to a
cluster of diseases that may occur in and impact any portion of
the human body. Cancers are sometimes also referred to as ma-
lignant tumors and neoplasms. The single most distinguishing
cancer feature is metasizing. It is the speedy origin of anomalous
cells, which propagate afar than their typical limits, and then
attack and extend to adjacent body parts. Internationally, cancer
is acknowledged as the second foremost reason of demises. It
accounted for approximately 9.6 million deaths in 2018. World-
wide, around one in six deaths is caused by cancer [1]. This dis-
turbing number of mortalities is a result of delayed cancer
detection, late medical attention, or from patients losing the drive
to live due to a prolonged and unrelenting treatment course.
Worldwide, now governments are taking steps to ensure timely
cancer detection and treatment. Conversely, diminutive attention
is being paid to the interminable treatment course affecting the
patient's mental health, defeating the patient's willpower to live.
In this chapter, we propose an approach for depression detection
in cancer communities using deep learning and natural language
processing (NLP). We illustrate the different deep learning models
that can be used for this task.
Depression is a mental disorder which is defined as a “condi-
tion characterized by a clinically significant disturbance in an
individual's cognition, emotion regulation, or behavior that re-
flects a dysfunction in the psychological, biological, or

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