Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity.
Irene Dankwa-MullanDilhan WeeraratnePublished in: Cancer discovery (2022)
Artificial intelligence (AI) and machine learning (ML) technologies have not only tremendous potential to augment clinical decision-making and enhance quality care and precision medicine efforts, but also the potential to worsen existing health disparities without a thoughtful, transparent, and inclusive approach that includes addressing bias in their design and implementation along the cancer discovery and care continuum. We discuss applications of AI/ML tools in cancer and provide recommendations for addressing and mitigating potential bias with AI and ML technologies while promoting cancer health equity.
Keyphrases
- artificial intelligence
- machine learning
- big data
- healthcare
- deep learning
- papillary thyroid
- quality improvement
- squamous cell
- public health
- decision making
- human health
- affordable care act
- small molecule
- primary care
- mental health
- lymph node metastasis
- health information
- climate change
- childhood cancer
- risk assessment
- social media