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3 papers
Automatic identification of diagnosis from hospital discharge letters via weakly supervised Natural Language Processing
Vittorio Torri, Elisa Barbieri, Anna Cantarutti +2
Identifying patient diagnoses from hospital discharge letters is essential for large-scale cohort selection and epidemiological research, but traditional supervised approaches requ…
An Unsupervised Natural Language Processing Pipeline for Assessing Referral Appropriateness
Vittorio Torri, Annamaria Bottelli, Michele Ercolanoni +2
Objective: Assessing the appropriateness of diagnostic referrals is critical for improving healthcare efficiency and reducing unnecessary procedures. However, this task becomes cha…
Interpretable phenotyping of Heart Failure patients with Dutch discharge letters
Vittorio Torri, Machteld J. Boonstra, Marielle C. van de Veerdonk +6
Objective: Heart failure (HF) patients present with diverse phenotypes affecting treatment and prognosis. This study evaluates models for phenotyping HF patients based on left vent…