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Artificial Intelligence (AI) has become a priority for healthcare organizations (HCOs), yet many AI and machine learning (ML) models fail to reach production. This is due to healthcare-specific challenges, such as defining episodes of care and ensuring clinical adoption of predictions. To ensure successful AI/ML models, HCOs must hone their focus, build a strong data foundation, and ensure clinical adoption. Additionally, they must also consider the ethical implications of AI and ensure the technology is used to drive positive change.
