Diaries

Inspiration

• Intervene in the early stage of mental health illness (if any) else connect to medical professionals
• To reduce information overload
• To require minimum user effort

What it does

Provoke sense of achievement

• Through to do lists

Collects mental health data through cleverly formed to-do-lists

• Sleeping, Eating, Exercise Patterns and more all pertaining to the user

Connect to medical health professionals

• Provide both parties with valuable insights on crucial user attributes
• More effective & less costly both for user and medical professionals

How we built it

• Reading research papers pertaining to mental health to get the basic sketch of the software
• Built website first and connect it with the machine learning classifier model
• Test the software

Challenges we ran into

• Finding proper datasets to train machine learning models
• Designing the software to require minimum user effort and reduce information burden to user

Accomplishments that we're proud of

• The way it leverages machine learning to make everyone feel a little better about themselves
• The way it should gets better with more users joining the platform
• The simple and novel way to key user attributes like eating, exercising, sleeping, etc without anyone ever feeling burdened
• Privacy respect

What we learned

• The fact that the dataset should be diverse to reduce bias
• Machine learning models perform best in the domain the dataset belongs
• Most websites today are designed to deluge users with information pushing them into depression

What's next for Diaries

• Better dataset
• More visualization
• Even less clutter and reduction of user intervention

Built With

• python