@inproceedings{fong-etal-2026-chirpe,
    title = "{CH}i{RPE}: A Step Towards Real-World Clinical {NLP} with Clinician-Oriented Model Explanations",
    author = "Fong, Stephanie  and
      Wang, Zimu  and
      Oliveira, Guilherme C  and
      Zhao, Xiangyu  and
      Jiang, Yiwen  and
      Liu, Jiahe  and
      Colton, Beau-Luke  and
      Woods, Scott W.  and
      Shenton, Martha  and
      Nelson, Barnaby  and
      Ge, Zongyuan  and
      Dwyer, Dominic",
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\'i}s",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 2: Short Papers)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.eacl-short.46/",
    pages = "646--658",
    ISBN = "979-8-89176-381-4",
    abstract = "The medical adoption of NLP tools requires interpretability by end users, yet traditional explainable AI (XAI) methods are misaligned with clinical reasoning and lack clinician input. We introduce CHiRPE (Clinical High-Risk Prediction with Explainability), an NLP pipeline that takes transcribed semi-structured clinical interviews to: (i) predict psychosis risk; and (ii) generate novel SHAP explanation formats co-developed with clinicians. Trained on 944 semi-structured interview transcripts across 24 international clinics of the AMP-SCZ study, the CHiRPE pipeline integrates symptom-domain mapping, LLM summarisation, and BERT classification. CHiRPE achieved over 90{\%} accuracy across three BERT variants and outperformed baseline models. Explanation formats were evaluated by 28 clinical experts who indicated a strong preference for our novel concept-guided explanations, especially hybrid graph-and-text summary formats. CHiRPE demonstrates that clinically-guided model development produces both accurate and interpretable results. Our next step is focused on real-world testing across our 24 international sites."
}