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New synthetic dataset AnchorSIPS aids AI psychosis-risk assessment

Researchers have developed AnchorSIPS, a synthetic dataset designed to overcome data access limitations in AI research for psychosis-risk assessment. This dataset comprises 10,000 structured interviews modeled after the Mini-SIPS clinical interview, capturing detailed patient histories, symptom responses, and diagnostic decisions. AnchorSIPS utilizes a plan-then-realize pipeline, employing an LLM to generate patient utterances within a controlled framework to ensure consistency and provide transcript-grounded evidence for each decision. The dataset aims to facilitate research in areas such as evidence extraction and transcript-grounded measurement. AI

IMPACT Enables AI research into psychosis-risk assessment by providing a privacy-preserving synthetic dataset.

RANK_REASON The cluster contains an academic paper detailing a new synthetic dataset for AI research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New synthetic dataset AnchorSIPS aids AI psychosis-risk assessment

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Guilherme C. Oliveira, Stephanie Fong, Zimu Wang, Clarice Lee, Xiangyu Zhao, Duy Khoa Pham, Duong Nhu, Yiwen Jiang, Jiahe Liu, Zhongxing Xu, Dwarikanath Mahapatra, Dominic Dwyer, Zongyuan Ge ·

    AnchorSIPS: A Synthetic Dataset and Evaluation Resource for Evidence-Supported Psychosis-Risk Symptom Measurement

    arXiv:2608.12329v1 Announce Type: cross Abstract: Progress on AI for psychosis-risk assessment is limited by a data-access bottleneck. Real clinical interviews are difficult to share because of privacy, governance, and consent constraints. We present AnchorSIPS, a synthetic datas…