Systematic Review of AI-Enhanced Oncology Multidisciplinary Teams

29 peer-reviewed studies from 2020 to 2026 are synthesized in this systematic review. It evaluates the clinical efficacy and socioeconomic implications of integrating artificial intelligence into oncology multidisciplinary team decision-making. The review was authored by Shuang Liu and last updated in May 2026.

Use Cases

• Benchmarking AI-human concordance rates in clinical decisions based on the reported 62-76% agreement range.
• Analyzing the socioeconomic benefits of AI in oncology based on described reductions in MDT preparation time.
• Investigating the limitations of AI in complex, individualized cancer cases as highlighted in the review findings.
• Evaluating AI's role in standardizing guideline-adherent treatment recommendations as described.

Strengths

• Synthesizes evidence from 29 peer-reviewed studies.
• Provides a specific temporal coverage from 2020 to 2026.
• Reports concrete AI-human concordance rates of 62-76%.

Limitations

• The dataset is a 10.8 KB document, indicating a very limited scope of raw data.
• Column-level documentation is absent; field semantics must be inferred after download.
• The review's conclusions are based on a specific set of 29 studies, which may not be exhaustive.

Provenance

Source

figshare

Collection Method

Systematic review of published literature.

Time Range

2020–2026

Freshness

Last updated 2026-05-25 04:43:20