Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity
73
Zitationen
2
Autoren
2022
Jahr
Abstract
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.
Ähnliche Arbeiten
A survey on deep learning in medical image analysis
2017 · 13.595 Zit.
Dermatologist-level classification of skin cancer with deep neural networks
2017 · 13.204 Zit.
A survey on Image Data Augmentation for Deep Learning
2019 · 11.823 Zit.
QuPath: Open source software for digital pathology image analysis
2017 · 8.202 Zit.
Radiomics: Images Are More than Pictures, They Are Data
2015 · 8.026 Zit.