arXiv:2606. 06235v1 Announce Type: new Abstract: Mortality forecasting plays an important role in actuarial and policy decision-making, but its implementation remains technically complex and inaccessible to non-expert users.
By Thi Kim Ngan Nguyen
arXiv:2608.23058v1 Announce Type: new
Abstract: Large language models (LLMs) now support forecasting systems that combine language-based reasoning with temporal data, evidence retrieval, external too...
By Xiaogang Xu, Jiaqi Tang, Jianmin Chen, Yingying Yan, Zhenchao Tang, Xiangxin Zhou, Xiaobin Hu, Wei Wei, Jinfeng Wu, Qifeng Chen, Lu Zhou, Jiafei Wu, Zhe Liu, Jianwei Yin, Weimin Zheng
SSMCGM-Stream is a streaming state‑space model designed for personalized diabetes management. It updates a hidden state with each new glucose reading, enabling constant‑time forecasting, physiologically structured counterfactual reasoning, and interpretable forecasts via hidden‑state attribution. The model, evaluated on the T1DEXI cohort, matches strong neural baselines in accuracy while significantly lowering computational cost, making continuous on‑device decision support feasible.
By Shakson Isaac, Chirag Patel
The paper introduces Empirical Research Assistance (ERA), an autonomous system that employs Large Language Model‑guided tree search to create, evaluate, and refine executable forecasting software for infectious diseases. In a real‑time evaluation during the 2025‑26 U.S. respiratory season, ERA produced diverse models for influenza, COVID‑19, and RSV, and an ensemble of these models outperformed the CDC’s gold‑standard forecast ensembles across all three pathogens. ERA also demonstrated robustness in data‑scarce RSV scenarios and showed that higher‑tier language models and specific optimization metrics can improve forecast accuracy.
By Sarah Martinson, Michael P. Brenner, Martyna Plomecka, Brian P. Williams, Nicholas G. Reich, Zahra Shamsi
arXiv:2606. 19183v1 Announce Type: cross Abstract: Large language models (LLMs) can make clinical decision support more accessible by interpreting free-text documentation, but their direct use as diagnostic engines is limited by sensitivity to prompts, information order, and plausible but incorrect outputs.
By Soheyl Bateni, Maryam Abdolali
arXiv:2606. 09852v1 Announce Type: cross Abstract: High-quality source code documentation is vital yet often neglected, especially in critical domains like healthcare where reliability and maintainability are essential.
By Ikbel Ghrab, Mohamed Dhieb, Ismail Khenissi, Ines Abdeljaoued-Tej