Developing the CAM-BERT: Enhancing delirium screening in hospitalized older adults using natural language processing.

Journal: Computers in biology and medicine
Published Date: Jul 16, 2025

Abstract

BACKGROUND: Delirium is a common condition affecting hospitalized older adults, often leading to adverse outcomes. Nevertheless, delirium frequently goes unrecognized due to various clinical and systemic challenges. We aimed to develop and evaluate a deep-learning natural language processing (NLP) model trained on Brazilian Portuguese clinical notes, aiming to improve the identification of delirium symptoms in electronic health records (EHR) and to facilitate the detection of delirium.

Authors

  • Cesar Gomes Miguel
    Hospital Israelita Albert Einstein, Sao Paulo, Brazil.
  • José Adenaldo Santos Bittencourt
    Hospital Israelita Albert Einstein, Sao Paulo, Brazil.
  • Leonardo Daniel Tavares
    Hospital Israelita Albert Einstein, Sao Paulo, Brazil.
  • Bárbara Vidra
    Faculdade Israelita de Ciências da Saude Albert Einstein, Sao Paulo, Brazil.
  • Murilo Gleyson Gazzola
    Hospital Israelita Albert Einstein, Sao Paulo, Brazil; Universidade Presbiteriana Mackenzie, Sao Paulo, SP, Brazil.
  • Tatianna Pinheiro da Costa Rozzino
    Hospital Israelita Albert Einstein, Sao Paulo, Brazil.
  • Thiago Junqueira Avelino-Silva
    Laboratorio de Investigacao Medica em Envelhecimento (LIM-66), Servico de Geriatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, SP, Brazil; Division of Geriatrics, University of California San Francisco, San Francisco, CA, United States; Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, USA and Trinity College Dublin, Dublin, Ireland.
  • Claudia Szlejf
    Hospital Israelita Albert Einstein, Sao Paulo, Brazil. Electronic address: claudia.jerussalmy@einstein.br.

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