harmonydata/mental_health_harmonisation_1
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Harmony
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At Harmony, we leverage the power of AI and natural language processing to streamline the retrospective harmonisation of questionnaire data across studies. Our cutting-edge NLP models help researchers compare, align, and integrate diverse mental health measures, ensuring consistency and compatibility across multilingual datasets. By applying transformer-based architectures, we enable more precise data mapping without relying on rigid dictionaries, making it easier to identify equivalent, similar, or contrasting questionnaire items across different languages and contexts. Through AI-driven harmonisation, we empower researchers to unlock deeper insights from existing data, fostering collaboration and advancing mental health research globally.
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