Explainability of artificial neural network in predicting career fulfilment among medical doctors in developing nations: Applicability and implications.

Journal: Social science & medicine (1982)
PMID: 39299154

Abstract

BACKGROUND: Career fulfilment among medical doctors is crucial for job satisfaction, retention, and healthcare quality, especially in developing nations with challenging healthcare systems. Traditional career guidance methods struggle to address the complexities of career fulfilment. While recent advancements in machine learning, particularly Artificial Neural Network (ANN) models, offer promising solutions for personalized career predictions, their applicability, interpretability, and impact remain challenging.

Authors

  • Dara Thomas
    Business School, Sichuan University, Sichuan, China; Global Organization of African Academic Doctors (OAAD), P.O. Box 14833-00100, Langata, Nairobi, Kenya. Electronic address: 2022521081004@stu.scu.edu.cn.
  • Ying Li
    School of Information Engineering, Chang'an University, Xi'an 710010, China.
  • Chiagoziem C Ukwuoma
    School of Software Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
  • Joel Dossa
    Business School, Sichuan University, Sichuan, China. Electronic address: 2022521081028@stu.scu.edu.cn.

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