Ensuring AI Success in Healthcare: The Vital Role of ML Monitoring

The healthcare industry is increasingly relying on artificial intelligence (AI) for disease diagnosis, patient outcome predictions, and overall patient care. With the growing reliance on AI systems, it's important to acknowledge that the likelihood of bad or changing data resulting in incorrect predictions or recommendations also increases. Healthcare companies need to keep an eye on the well-being of their models and the quality of the data used to train and update them to ensure their AI systems are performing as expected. Key reasons for implementing an ML monitoring solution include identifying issues before they become serious problems, improving patient outcomes, reducing costs, and ensuring compliance and regulation.