[Early Prediction of Support Necessity for Pharmacy Clinical Internship Using Deep Learning]

Yakugaku Zasshi. 2023;143(8):647-653. doi: 10.1248/yakushi.22-00203.
[Article in Japanese]

Abstract

The duration of undergraduate study was extended in 2006 to six years for pharmaceutical education aimed at training highly qualified pharmacists. Clinical internship in current pharmaceutical education is positioned as being important for fostering the qualities required of a pharmacist, and the support of faculty members is essential. Based on the above, we thought that support from faculty members should be provided easily and positively, which would enrich community pharmacy clinical internships. This study aimed to examine the method of predicting the need for support from weekly reports of community pharmacy practice trainees at Showa Pharmaceutical University. It became evident that the level of necessary support could not be predicted by using the support needs listed. However, application of deep learning to the contents of the weekly report for the first to fifth weeks in 2019 enabled the prediction of the level of support needed in 2020 with 97% accuracy. Although this research is currently limited to predicting the level of support required for community pharmacy practical internship at our university, it demonstrates the use of deep learning to predict the level of support needed based on five weeks' worth of weekly reports.

Keywords: clinical internship; deep learning; support necessity; weekly report.

Publication types

  • English Abstract

MeSH terms

  • Curriculum
  • Deep Learning*
  • Education, Pharmacy*
  • Humans
  • Internship and Residency*
  • Pharmacists
  • Pharmacy*