How artificial intelligence helps depression detection?

KellyOnTech
3 min readFeb 18, 2021

Today I will discuss how AI can help with depression detection. The current news is reporting on the increase of depression and the increase in the number of suicides around the world.

Every year, one in 10 people in the world suffers from varying degrees of depression. Depression is the main cause of disability for people in the 15–44 age group. Every 13 minutes, someone in a corner of the world commits suicide because of depression.

Depression quick facts
Image source: https://www.hopefordepression.org/depression-facts/

The causes of depression are very complicated, and there are many patients who behave normally or pretend to be normal in most cases. There is a symptom of depression called “smiling depression”, which refers to the fact that although the patient is depressed or anxious, he still pretends to be smiling face as if wearing a mask.

Artificial intelligence helps predict depression currently in two categories:

  1. Judge the risk of illness by analyzing language style and language coherence
  2. By tracking and analyzing people’s micro-expression, micro-behaviour, and subtle tone changes

At present, the most popular artificial intelligence solution is a team composed of members of IBM Research’s computational psychiatry and neuroimaging team and universities around the world, using natural language processing NLP artificial intelligence (AI) methods to detect problems in patient language, and whether patients’ language and their thought expression matches. The patient’s psychosis can be assessed and predicted relatively accurately, with an accuracy rate of 83%.

IBM Research depression detection report
Source: IBM Research depression detection report

In October 2020, IBM Research improved the previous system. Seven researchers including Pengwei Hu, Ph.D. and Hui Su of the Hong Kong University of Science and Technology proposed a new system called BlueMemo for social media screening of patients with depression. Based on the real-time posts collected from Twitter, the research team extracted the learned text features, image features, and visual attributes into three modalities, and input them into the multi-modal fusion and classification model to improve the accuracy of the system.

IBM Research BlueMemo project
Source: IBM Research BlueMemo project

Depression is difficult to cure. Even if the patient receives psychotherapy and can return to a normal mental state, there is still a high recurrence.

Therefore, the prevention of depression is particularly important. Especially during the COVID-19 pandemic, everyone is affected by changes in school, work, life and entertainment, and the number of patients with depression has also increased significantly. Here is a special reminder that parents with children, while caring about their children eating, sleeping, and doing homework, please spend time and energy to truly accompany them. It is very necessary to relieve their negative emotions. Don’t wait until it’s too late!

I prepared a video for your reference.

About KellyOnTech

KellyOnTech is dedicated to explaining the global cutting-edge technology and scientific research projects of major universities in a simple and easy-to-understand language, introducing global technology companies, so as to help you better understand technology trends and discover investment opportunities.

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KellyOnTech

Tech Investor / Founder at Mans International / Author