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

Author

Listed:
  • Thomas, Dara
  • Li, Ying
  • Ukwuoma, Chiagoziem C.
  • Dossa, Joel

Abstract

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.

Suggested Citation

  • Thomas, Dara & Li, Ying & Ukwuoma, Chiagoziem C. & Dossa, Joel, 2024. "Explainability of artificial neural network in predicting career fulfilment among medical doctors in developing nations: Applicability and implications," Social Science & Medicine, Elsevier, vol. 360(C).
    • Handle: RePEc:eee:socmed:v:360:y:2024:i:c:s0277953624007834
    DOI: 10.1016/j.socscimed.2024.117329
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