Depression: an interactive clinical scenario made with twine 2.0 Harlowe format
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Updated
Oct 9, 2024 - HTML
Depression: an interactive clinical scenario made with twine 2.0 Harlowe format
Depression detection using machine learning is a vital area of research given the global burden of mental health disorders. This project explores two primary methodologies: leveraging depression quiz tests and analyzing sentences.
Wearable-derived sleep features predict relapse in Major Depressive Disorder
Brotherly Health - "digital behavioural change therapy" || Online platform for managing anxiety and depression using cognitive behavioural therapy || Tech Stack: HTML / CSS / JavaScript
Analysis of regulatory impacts of GWAS SNPs associated with psychiatric disorders and cognitive functioning.
Data and code supporting "An Online Cultural Experience for Mental Health in People Aged 16-24 Compared to a Typical Museum Website: A Randomised Controlled Trial"
Keep track of your mental health
A failed and futile effort to not fail My A levels and not get shouted at by Mr Harris BSc
Awarded Best UI/UX Design, a Top 10 Project at SFU StormHacks 2022 | panic attack first-aid made simple.
PHQ-9 (Patient Health Questionnaire-9) Objectifies degree of depression severity (Polish version).
Edinburgh Postnatal Depression Scale (EPDS), Polish version
A visual representation of depressive thoughts.
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