Mental health analysis of cancer-diagnosed patients with the lowest survival rate and their caregivers

Abstract

Throughout the world, millions of people and their families are impacted by the serious illness of cancer. The total number of new cancer cases worldwide in 2020 was predicted to reach 18.1 million. Serious emotional disorders, like depression, are often present in cancer patients due to many factors, including the intensity of certain situations, the negative consequences of their long treatment, or the deaths of other cancer patients. Therefore, keeping an eye on the patient’s moods is crucial to their ongoing treatment. Many cancer patients use online social media sites such as Facebook and Twitter to communicate their thoughts and emotions about their treatments, as well as the difficulties associated with them, in the form of posts or messages. From these sources, we can get good information about the mood of those patients, which will further help us with their treatment. After applying the necessary pre-processing to this data, we can apply sentimental analysis methods, which will help us predict the positive or negative emotions of cancer patients on these online platforms. We can give better psychological support to these patients after analyzing their mental health. So, our objective is to design a model capable of identifying such actions, as among all the cancers we are working on, five have the lowest survival percentage.