Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure
arXiv:2606.17441v1 Announce Type: cross Abstract: Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and expensive user studies. However, existing approaches often lack realism and controllability, often oversharing information unprompted, and failing to capture the wide variability of patient behavior. Here, we introduce PatientsWithPersonality (PWP), a patient simulation framework that generates realistic yet diverse virtual patient responses through explicit personality parametrization over a latent patient
The rapid advancement of large language models (LLMs) requires robust and scalable testing methods, particularly in critical applications like healthcare. This research addresses the immediate need for more realistic and controllable simulation environments to accelerate LLM development and deployment in clinical settings.
A strategic reader should care because realistic patient simulation significantly reduces the cost and time associated with user studies for clinical AI applications. This accelerates the development and safe deployment of AI in healthcare, impacting efficiency and patient care.
The ability to generate diverse and controllable virtual patient responses marks a significant improvement over previous simulation methods, enabling more comprehensive and targeted testing of LLMs. This changes how clinical AI is developed and validated.
- · AI developers in healthcare
- · Healthcare systems adopting AI
- · Patients receiving AI-assisted care
- · Academic research institutions
- · Traditional clinical trial methodologies
- · Companies relying on less sophisticated simulation
- · Patients of systems slow to adopt validated AI
More efficient and cost-effective development of clinical AI applications.
Faster integration of validated AI tools into medical practice, improving diagnostic and treatment pathways.
Ethical considerations around the potential for 'black box' AI in patient interactions become more critical as AI autonomy increases.
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Read at arXiv cs.AI