Integrating artificial intelligence (AI) into healthcare reshapes clinical practices and revolutionizes how patient data is evaluated and managed. This Methods Collection highlights groundbreaking advancements in AI applications, ranging from surgical innovations to predictive data analytics. By utilizing machine learning, AI-driven decision systems, and big data techniques, healthcare professionals can improve precision, reduce procedural risks, and deliver more personalized, proactive care. The collection showcases contributions that explore AI's transformative role in real-time clinical settings and long-term health data analysis.

Key topics include AI in robot-assisted surgeries, image-guided interventions, and personalized treatment planning. The collection also delves into the application of AI in health data evaluation, exploring how electronic health records (EHRs), wearable devices, and medical imaging data can be leveraged to predict outcomes, improve diagnostics, and inform decision-making. Additionally, it will focus on predictive models for disease progression and the ethical implications surrounding AI's role in healthcare. This comprehensive collection aims to serve as a critical resource for surgeons, data scientists, AI researchers, and policymakers, advancing the future of AI-powered healthcare and clinical innovation.