Explainable, trustworthy, and ethical machine learning for healthcare: A survey

Explainable, trustworthy, and ethical machine learning for healthcare: A survey

<p dir="ltr">With the advent of machine learning (ML) and deep learning (DL) empowered applications for critical applications like healthcare, the questions about liability, trust, and interpretability of their outputs are raising. The black-box nature of various DL models is a roadb...

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Bibliographic Details
Main Author: Khansa Rasheed (17380573) (author)
Other Authors: Adnan Qayyum (16875936) (author), Mohammed Ghaly (17380576) (author), Ala Al-Fuqaha (4434340) (author), Adeel Razi (17380579) (author), Junaid Qadir (16494902) (author)
Published: 2022
Subjects:
Health sciences
Health services and systems
Information and computing sciences
Machine learning
Software engineering
Philosophy and religious studies
Applied ethics
Explainable machine learning
Interpretable machine learning
Trustworthiness
Healthcare
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