The significance of using machine learning in healthcare diagnostics lies in its ability to analyze vast amounts of data for improved accuracy in diagnosis. Machine learning algorithms can identify patterns and correlations within medical data that may not be apparent to human practitioners. This leads to earlier detection of diseases, personalized treatment plans, and better patient outcomes. By leveraging historical patient data, machine learning enhances predictive analytics, allowing for proactive health management and optimized resource allocation, ultimately resulting in a more efficient healthcare system.