AI-enhanced oncology MDT 2.0: from multi-modal data synergy to value-based care reconstruction - a systematic review of clinical efficacy and socioeconomic benefits - Summary - MDSpire

AI-enhanced oncology MDT 2.0: from multi-modal data synergy to value-based care reconstruction - a systematic review of clinical efficacy and socioeconomic benefits

  • By

  • Shuang Liu

  • Hetong Wang

  • Lijie He

  • May 25, 2026

  • 0 min

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Objective:

To evaluate the clinical efficacy and socioeconomic implications of integrating AI into oncology multidisciplinary team (MDT) decision-making.

Key Findings:
  • AI systems achieved concordance rates with human tumor boards of 62-76% across multiple cancer types.
  • Substantial agreement in guideline-driven decisions but limitations in complex, individualized cases.
  • AI demonstrates strengths in standardizing guideline-adherent recommendations and supporting molecular target identification.
  • AI struggles with nuanced clinical judgment and patient-specific factors.
  • AI offers potential for value-based care reconstruction through reduced MDT preparation time and democratized access to subspecialty expertise.
Interpretation:

Limitations:
  • Rigorous cost-effectiveness evidence remains limited.
  • Heterogeneity in study designs and AI models complicates direct comparisons.
Conclusion:

AI integration in oncology MDTs shows potential in enhancing decision-making and access.

Original Source(s)

AI-enhanced oncology MDT 2.0: from multi-modal data synergy to value-based care reconstruction - a systematic review of clinical efficacy and socioeconomic benefits

  • by Shuang Liu, Hetong Wang, Lijie He

  • May 25, 2026

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