Synthetic data: How could it be used for infectious disease research?

TL;DR

Synthetic data generated by AI offers promising benefits for infectious disease research, including enhanced privacy, reduced bias, and new research opportunities, despite concerns about misuse and ethical issues.

Contribution

This paper provides an overview of how synthetic data, especially from generative AI, can be utilized to advance infectious disease research and discusses future prospects.

Findings

Synthetic data improves data privacy in healthcare research.

Generative AI enables creation of diverse synthetic datasets.

Potential for synthetic data to reduce bias in disease modeling.

Abstract

Over the last three to five years, it has become possible to generate machine learning synthetic data for healthcare-related uses. However, concerns have been raised about potential negative factors associated with the possibilities of artificial dataset generation. These include the potential misuse of generative artificial intelligence (AI) in fields such as cybercrime, the use of deepfakes and fake news to deceive or manipulate, and displacement of human jobs across various market sectors. Here, we consider both current and future positive advances and possibilities with synthetic datasets. Synthetic data offers significant benefits, particularly in data privacy, research, in balancing datasets and reducing bias in machine learning models. Generative AI is an artificial intelligence genre capable of creating text, images, video or other data using generative models. The recent explosion of interest in GenAI was heralded by the invention and speedy move to use of large language models (LLM). These computational models are able to achieve general-purpose language generation and other natural language processing tasks and are based on transformer architectures, which made an evolutionary leap from previous neural network architectures. Fuelled by the advent of improved GenAI techniques and wide scale usage, this is surely the time to consider how synthetic data can be used to advance infectious disease research. In this commentary we aim to create an overview of the current and future position of synthetic data in infectious disease research.