A landmark systematic review has revealed that quantum computing applications in healthcare remain more theoretical than practical, despite growing excitement in the field.
The comprehensive study, which analysed 4,915 research papers published between 2015 and 2024, found little evidence that quantum machine learning (QML) algorithms currently offer any meaningful advantage over classical computing methods for healthcare applications.
"Despite exponential growth in research claiming quantum benefits for healthcare, our analysis shows no consistent evidence that quantum algorithms outperform classical methods for clinical decision-making or health service delivery," said Dr Riddhi Gupta from the School of Mathematics and Physics and the Queensland Digital Health Centre (QDHeC) at the University of Queensland.
The review identified several critical gaps in current research approaches:
- Only 16 of 169 eligible studies actually tested their algorithms under realistic quantum hardware conditions, with most relying solely on idealised simulations
- Most research failed to address critical factors like noise characterisation, error mitigation, or performance scaling as problem size increases
- Applications were narrowly focused on clinical diagnosis and prediction, with minimal exploration of health service delivery or public health applications
- Data encoding scalability remains problematic, often requiring hardware assumptions that don't exist in current quantum systems
Dr Gupta said that while quantum computing holds tremendous theoretical promise for healthcare, this review provides an important reality check on the current state of the technology.
"The field needs to address these methodological challenges before quantum methods can deliver meaningful advantages in health data processing,” she said.
The researchers propose new standards for evaluating quantum computing applications in healthcare, including minimum requirements for demonstrating scalability and performance under realistic conditions.
QDHeC’s Deputy Director, Professor Jason Pole said that this study confirms that while quantum technology is promising, it is not going to change healthcare next week.
“Decision makers get understandably excited when we talk about the possibilities of quantum computing in healthcare, but Dr Gupta’s study affirms that we still have a lot of work to do before we can apply this technology in a useful and strategic way.”
Senior author of the study, Associate Professor Sally Shrapnel who leads the QDHeC Quantum Program and is Deputy Director of the Australian Research Council’s Centre of Excellence for Engineered Quantum Systems (EQUS) says that despite these challenges, researchers are optimistic about the future of quantum computing in healthcare.
“This review captures the current state of play, but the field is advancing rapidly with impressive progress from both universities and companies,” she said.
“I have no doubt we will see exciting quantum application in digital healthcare in the future.”
Read the full paper here – A systematic review of quantum machine learning for digital health | npj Digital Medicine
