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The Application of Design Thinking in Developing a Deep Learning Algorithm for Hip Fracture Detection.

Chun-Hsiang Ouyang1, Chih-Chi Chen2, Yu-San Tee1

  • 1Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital, Chang Gung University, Linkou, Taoyuan 33328, Taiwan.

Bioengineering (Basel, Switzerland)
|June 28, 2023
PubMed
Summary
This summary is machine-generated.

Design thinking improved deep learning (DL) algorithms for trauma care by focusing on clinical needs. This user-centered approach enhanced diagnostic accuracy in detecting femoral fractures from pelvic X-rays.

Keywords:
artificial intelligencedeep learningdesign thinkinghip fracturetrauma

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence in Healthcare
  • Clinical Decision Support

Background:

  • Deep learning (DL) shows promise in clinical practice but faces integration challenges.
  • Design thinking offers a user-centered problem-solving framework applicable to healthcare.

Purpose of the Study:

  • To apply design thinking principles to develop and refine a DL algorithm for clinical use.
  • To enhance the performance and clinical applicability of a DL algorithm for trauma care.

Main Methods:

  • Design thinking was employed, involving interviews with clinical doctors to understand needs.
  • A DL algorithm using the Xception convolutional neural network was developed for hip fracture detection from pelvic X-rays (PXRs).
  • DL model performance was compared before and after integrating design thinking insights.

Main Results:

  • The study identified the need to reduce misdiagnosis of femoral fractures in emergency settings.
  • A dataset of 4235 PXRs was used, with 2146 (51%) showing hip fractures.
  • Design thinking integration improved diagnostic accuracy from 0.91 to 0.95, sensitivity from 0.97 to 0.97, and specificity from 0.84 to 0.93.

Conclusions:

  • Design thinking ensures DL solutions are user-centered for trauma care.
  • This approach effectively meets the needs of both patients and healthcare providers.
  • The study highlights the value of design thinking in optimizing DL deployment in clinical settings.