Artificial intelligence across the cancer care continuum

Area of Science:

• Oncology
• Artificial Intelligence
• Medical Informatics

Background:

• Artificial intelligence (AI) presents transformative potential across the entire cancer care continuum.
• Current applications span risk assessment, early detection, treatment, and supportive care.
• AI integrates diverse data, including multi-omics and electronic health records, for personalized strategies.

Purpose of the Study:

• To provide a comprehensive overview of current and emerging AI applications in oncology.
• To highlight AI's role in enhancing cancer risk stratification, diagnosis, treatment, and survivorship.
• To discuss challenges and requirements for successful AI integration into clinical practice.

Main Methods:

• Review of current and emerging artificial intelligence applications in oncology.
• Analysis of AI's role in integrating multi-omics and electronic health records.
• Exploration of AI in medical image analysis, histopathology, treatment planning, and survivorship care.

Main Results:

• AI algorithms show promise in improving accuracy and efficiency in cancer screening, diagnosis, and treatment planning.
• AI can personalize prevention, optimize radiation therapy, and tailor systemic therapy selection.
• AI enhances clinical workflows, evidence dissemination, and patient-reported outcomes for decision support.

Conclusions:

• Successful AI integration requires addressing challenges like algorithm validation, data privacy, and bias mitigation.
• Interdisciplinary collaboration and healthcare professional education are essential for effective AI implementation.
• Synergistic interaction between AI and clinical expertise is key to realizing AI's potential in personalized cancer care.