Around 1 in 4 people will experience a mental health problem this year. Low-income countries have an estimated treatment gap of 85% (as compared with high-income countries with a gap of 35% to 50%). While Kenya has a mental illness prevalence rate that is comparable to that of high-income countries, there are still less than 500 healthcare professionals serving the country.

In Kenya, there are growing concerns about mental health among young people, particularly university students that face a challenging and unique conflation of stressors that put them at risk of challenges like depression and substance abuse.

From the use of app-based solutions for screening to electronically delivered therapies, the use of technologies including machine learning and AI will potentially transform the delivery of mental health services in the coming years.

The objective of this challenge is to develop a machine learning model that classifies statements and questions expressed by university students in Kenya when speaking about the mental health challenges they struggle with. The four categories are depression, suicide, alchoholism, and drug abuse.

This solution will be used for a prototype of a mental health chatbot designed specifically for university students. This initiative is a first step in leveraging technology to make mental health services more accessible and more user-friendly for young people in Kenya and around the world.

Basic Needs Basic Rights Kenya (Facebook page):

This challenge is sponsored by Basic Needs Basic Rights (BNBR) Kenya. BNBR supports people with or at increased risk of mental health problems to live and work successfully in their communities by facilitating access to mental health care and social support services.

Deep Learning Indaba

An indaba is a Zulu word for a gathering or meeting. Such meetings are held throughout southern Africa and serve several functions: to listen to and share the news of members of the community, to discuss common interests and issues facing the community, and to give advice and coach others. This is one of many words we have, including an imbizo (in Xhosa), an intlanganiso, and a lekgotla (in Sesotho). and by other words in other parts of the continent, such as a baraza (in Kiswahili) in Kenya and Tanzania, and padare (in Shona) in Zimbabwe. And of course, this connects us to community gatherings that are similarly held by cultures throughout the world.

This spirit of coming together, of sharing and learning, is one of the core values of our organization and, hence, the best choice of name for it.

The Kenya Medical Research Institute (KEMRI): https://www.kemri.go.ke

The Kenya Medical Research Institute (KEMRI) is a State Corporation established in Kenya in 1979 through the Science and Technology (Repealed) Act, Cap 250 of the Laws of Kenya operated under the Science Technology and Innovation Act, 2013 as the national body responsible for carrying out research in human health in Kenya. Currently, KEMRI operates under Legal Notice No. 35 of March 2021.

KEMRI has grown from its humble beginning over 40 years ago to become a regional leader in human health research. The Institute currently ranks as one of the leading Centres of excellence in health research both in Africa as well as globally. Our mission is to improve human health and quality of life through research, capacity building, innovation and service delivery.

Deep Learning IndabaX Kenya

This is a Chapter of Deep Learning Indaba in Kenya

Rules

As this is a learning challenge, aside from the rules in the Terms of Use, no other particular rules apply.

This challenge is open to IndabaX Kenya participants.

Teams and collaboration

You may participate in this competition as an individual or in a team of up to four people. When creating a team, the team must have a total submission count less than or equal to the maximum allowable submissions as of the formation date. A team will be allowed the maximum number of submissions for the competition, minus the highest number of submissions among team members at team formation.

Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. Individuals and their submissions originating from multiple accounts will be disqualified.

Code must not be shared privately outside of a team. Any code that is shared, must be made available to all competition participants through the platform. (i.e. on the discussion boards).

Datasets and packages

The solution must use publicly-available, open-source packages only. Your models should not use any of the metadata provided.

You may use only the datasets provided for this competition. Automated machine learning tools such as automl are not permitted.

If the challenge is a computer vision challenge, image metadata (Image size, aspect ratio, pixel count, etc) may not be used in your submission.

You may use pretrained models as long as they are openly available to everyone.

The data used in this competition is the sole property of Zindi and the competition host. You may not transmit, duplicate, publish, redistribute or otherwise provide or make available any competition data to any party not participating in the Competition (this includes uploading the data to any public site such as Kaggle or GitHub). You may upload, store and work with the data on any cloud platform such as Google Colab, AWS or similar, as long as 1) the data remains private and 2) doing so does not contravene Zindi’s rules of use.

You must notify Zindi immediately upon learning of any unauthorised transmission of or unauthorised access to the competition data, and work with Zindi to rectify any unauthorised transmission or access.

Your solution must not infringe the rights of any third party.

Submissions and winning

You may make a maximum of 3 submissions per day.

Note that to count, your submission must first pass processing. If your submission fails during the processing step, it will not be counted and not receive a score; nor will it count against your daily submission limit. If you encounter problems with your submission file, your best course of action is to ask for advice on the Competition’s discussion forum.

Note that there is no public/private leaderboard split for this challenge. Read more about public and private leaderboards in this post.

You acknowledge and agree that Zindi may, without any obligation to do so, remove or disqualify an individual, team, or account if Zindi believes that such individual, team, or account is in violation of these rules. Entry into this competition constitutes your acceptance of these official competition rules.

Zindi also reserves the right to disqualify you and/or your submissions from any competition if we believe that you violated the rules or violated the spirit of the competition or the platform in any other way. The disqualifications are irrespective of your position on the leaderboard and completely at the discretion of Zindi.

Please refer to the FAQs and Terms of Use for additional rules that may apply to this competition. We reserve the right to update these rules at any time.

The evaluation metric for this challenge is Log Loss.

The values can be between 0 and 1, inclusive. They do not have to add up to 1 across the classes.

ID       Depression   Alcohol   Suicide   Drugs
GVRCWM      0.63       0.98      0.21      0.12 
8NRRD6      0.76       0.11      0.56      0.67

This is a knowledge competition with 500 Zindi points.