Download PDFOpen PDF in browser

Ethical Considerations in Using Machine Learning for Healthcare Applications

EasyChair Preprint no. 13565

21 pagesDate: June 6, 2024


Machine learning (ML) has the potential to revolutionize healthcare by enabling advanced diagnostics, personalized treatments, and improved patient outcomes. However, the ethical implications of using ML in healthcare cannot be overlooked. This abstract explores the key ethical considerations that need to be addressed when applying ML in healthcare applications.


Privacy and data protection are crucial concerns in healthcare ML. Safeguarding patient data, obtaining informed consent, and implementing secure storage and transmission mechanisms are essential to maintain confidentiality and trust. Bias and fairness issues must also be addressed, including identifying and mitigating biases in training data, ensuring fairness in algorithmic decision-making, and providing transparency in the process.

Keyphrases: Accessibility, Equity, ethical review, fairness, Governance, Regulatory Compliance

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Godwin Olaoye},
  title = {Ethical Considerations in Using Machine Learning for Healthcare Applications},
  howpublished = {EasyChair Preprint no. 13565},

  year = {EasyChair, 2024}}
Download PDFOpen PDF in browser