Harmony News
We are pleased to announce that the Harmony REST API is now released. The source code is at https://github.com/harmonydata/harmonyapi and the API reference PDF can be seen at https://github.com/harmonydata/harmonyapi/blob/main/docs/API_reference.pdf. Meanwhile, you can install and run Harmony Python library with pip install harmonydata How does Harmony work in layman’s terms? Harmony compares questions from different instruments by converting them to a vector representation and calculating their similarity. You can read more at https://harmonydata.
Many psychologists believe that mental illnesses can vary across cultures. In 1904, Emil Kraepelin initiated the field of comparative psychiatry after studying mental health disorders in Java, writing that “Die Eigenart eines Volkes wird auch in der Häufigkeit und klinischen Gestaltung seiner Geistesstörungen zum Ausdruck kommen,” meaning “The peculiarity of a people[ethnic group] will also be expressed in the frequency and clinical form of its mental disorders.”[1] More than a century later, the emergence of global mental health research projects has opened a number of debates about the applicability of psychiatric categories to different cultural settings, such as those in the Diagnostic and Statistical Manual of Mental Disorders (DSM) series[2].
Harmony was able to reconstruct the matches of the questionnaire harmonisation tool developed by McElroy et al in 2020 with the following AUC scores: childhood 84%, adulthood 80%. Harmony was able to match the questions of the English and Portuguese GAD-7 instruments with AUC 100% and the Portuguese CBCL and SDQ with AUC 89%. Harmony was also evaluated using a variety of transformer models including MentalBERT, a publicly available pretrained language model for the mental healthcare domain.
The Wellcome Data Prize was recently featured on Smile 90.4FM, a radio station in South Africa. In this episode, Inês Pote discussed the Wellcome Data Prize in Mental Health. Wellcome is on the lookout for teams that develop innovative ways to use data to improve the prevention, treatment, and management of anxiety and depression in young people in South Africa.
5 key things Implementation Science has taught us to focus on Yesterday the Harmony team received the wonderful news that we are given the chance to continue working on Harmony for another six months, after which we can put ourselves forward for the final round. The Wellcome Mental Health Data Prize has chosen an unusual (for the research world) approach this time, using a “Dragon’s Den” style scheme where research teams can pitch their ideas to win funding for their projects.
Semantic text matching is a task in natural language processing involving estimating the semantic similarity between two texts. For example, if we had to quantify the similarity between “I feel nervous” and “I feel anxious”, most people would agree that these are closer together than either sentence is to “I feel happy”. A semantic text matching algorithm would be able to place a number on the similarity, such as 79%.
