The paper presents EpidemIA, a training‑free AI Multi Agent System that lets clinicians and administrators use epidemiological models and perform statistical analyses through natural language conversations. The system runs on a single‑GPU workstation, employs a locally hosted open‑weights LLM to keep data private, and includes a modular suite of expert‑written models. Using Emergency Department visit data from IRCCS Sant’Orsola, the authors demonstrate that users can conduct both simple statistical queries and complex dynamical predictions via natural language.
The Epydemix Agent Framework adds an AI‑friendly layer to the Epydemix Python library for stochastic epidemic modeling. It provides four key features: model and parameter discovery, declarative scenario validation, execution via tested code, and result inspectability, enabling an AI agent to manage the entire modeling workflow from natural‑language input to quantitative outputs. The authors demonstrate the framework with a vaccination strategy case study and evaluate it over 50 agent sessions, showing reductions in turns, output tokens, and cost compared to direct Python use.
By Nicol\`o Gozzi, Ciro Cattuto, Alessandro Vespignani
arXiv:2610.34878v1 Announce Type: new
Abstract: Disease diagnosis is a key application of large language model (LLM) agents in healthcare. However, existing medical agents are primarily trained and e...
By Sirry Chen, Fangke Chen, Xuanwen Ding, Wei Chen, Zhongyu Wei
Disease diagnosis is a key application of large language model (LLM) agents in healthcare. However, existing medical agents are primarily trained and evaluated with static question-answering data, pro...
arXiv:2607. 06757v1 Announce Type: new Abstract: Agent-based modeling (ABM) has the capability to model millions of individuals and their interactions, which is useful for policy making.
By Sifat Afroj Moon, Dakotah Maguire, Adam Spannaus, Joe Tuccillo, Maksudul Alam, Sudip K. Seal, John Gounley, Heidi Hanson
arXiv:2608. 11420v1 Announce Type: new Abstract: Medical diagnostic reasoning is a high-impact use case for LLMs that carries significant implications for the health and wellbeing of users.
By Del Coburn, Scott Sanner, Dan Silver