ArticleFrontiers in digital health2022
Leveraging the potential of synthetic text for AI in mental healthcare.
Article in Frontiers in digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A review on generative AI models for synthetic medical text, time series, and longitudinal data.NPJ digital medicine · 2025Article
- Synthetic data as an investigative tool in hypertension and renal diseases research.World journal of methodology · 2025Article
- Open Science at the generative AI turn: An exploratory analysis of challenges and opportunities.Quantitative science studies · 2025Article
- Leveraging reddit data for context-enhanced synthetic health data generation to identify low self esteem.Frontiers in psychiatry · 2025Article
- Embracing the uncertainty in human-machine collaboration to support clinical decision-making for mental health conditions.Frontiers in digital health · 2023Article
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Authors and funding
1 author.
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Abstract
In today's world it seems fair to say that extensive digital data sharing is the price we pay for the technological advances we have seen achieved as a result of AI systems analysing large quantities of data in a relatively short time. Where such AI is used in the realm of mental health, this data sharing poses additional challenges not just due to the sensitive nature of the data itself but also the potential vulnerability of the data donors themselves should there be a cybersecurity data breach. To address the problem, the AI community proposes to use synthetic text preserving only the salient properties of the original. Such text has potential to fill gaps in the textual data availability (e.g., rare conditions or under-represented groups) while reducing exposure. Our perspective piece is aimed to demystify the process of generating synthetic text, explain its algorithmic and ethical challenges, especially for the mental health domain, as well as most promising ways of overcoming them. We aim to promote better understanding and as a result acceptability of synthetic text outside the research community.
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