Study Finds Success In Using Taiwanese Medication Safety AI Model For US' EHR Systems

Study Finds Success In Using Taiwanese Medication Safety AI Model For US' EHR Systems

The study also found that applying a federated learning approach can further improve accuracy of the model.
A study has demonstrated the international transferability of a Taiwanese artificial intelligence model for detecting medication errors in EHR systems in the United States.

The study was jointly conducted by Taiwan-based medical AI startup Aesop Technology, Taipei Medical University, Harvard Medical School and Brigham and Women's Hospital. Its results were announced last week in a press release.

WHY IT MATTERS

The "biggest challenge" in data-driven medicine is the successful implementation of data-driven applications in clinical practice from local to global settings without compromising patient safety and privacy, according to Dr Yu-Chuan Jack Li, a professor at Taipei Medical University.

The study, whose findings were published in the Journal of Medical Internet Research - Medical Informatics in January, found "good" transferability of Aesop's machine learning model in the EHR systems of two training schools under Harvard Medical School – Brigham and Women’s Hospital and Massachusetts General Hospital.


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