Which of the following is a common application of AI in healthcare?

AI for diagnostic predictions and personalizing treatment plans is a common and impactful application of AI in healthcare. This use of AI leverages large datasets, including patient histories, medical records, and clinical studies, to help healthcare providers make more accurate diagnoses and tailor treatments to individual patients. Machine learning algorithms can identify patterns in data that may not be immediately obvious to human practitioners, allowing for early detection of diseases and more effective management of chronic conditions.

By personalizing treatment plans, AI can consider a patient’s unique genetic makeup, lifestyle, and response to previous treatments, leading to improved outcomes and minimizing potential side effects. This integrative approach exemplifies the transformative potential of AI in enhancing patient care through data-driven insights.

In contrast, applications focused strictly on administrative tasks, patient scheduling, or drug discovery, while valuable, do not have the same level of direct impact on patient diagnostics and personalized healthcare as the implementation described in the correct answer. These applications tend to streamline operations or assist in specific aspects of healthcare but do not exhibit the extensive and nuanced engagement with patient care that effective AI-driven diagnostics and treatment personalization achieve.