{
  "abstract": "Objective To assess the clinical effectiveness and diagnostic accuracy of specific artificial intelligence (AI) systems with computer-aided polyp detection (CADe) and/or computer-aided polyp characterisation (CADx) functionalities.Methods and analysis Studies using CADe/CADx systems alongside endoscopist judgement during real-time colonoscopies for any indication were included from searches performed in June 2025. Adenoma detection rate (ADR) and diagnostic accuracy (eg, sensitivity and specificity) were key outcomes, with other polyp detection outcomes, procedural duration and adverse events (AEs) also analysed. For CADe, meta-analyses were stratified by each individual AI system. Meta-analyses were not performed for CADx due to heterogeneity concerns. Subgroup analyses for colonoscopy indication and endoscopist experience were explored.Results Overall, 52 studies (43 for CADe and 9 for CADx) covering eight CADe/CADx systems were included. ADR increased with each individual CADe system versus colonoscopy without CADe; results for two systems lacked statistical significance. While more uncertain, some systems also increased the detection of advanced and non-advanced adenomas, different-sized adenomas, sessile serrated lesions (SSLs) and/or hyperplastic/non-neoplastic polyps. Adjunct CADx diagnostic accuracy results were inconsistent and had limitations; comparisons against endoscopist optical diagnoses were often not available, SSLs were often analysed as non-neoplastic and low-confidence diagnoses were often excluded. CADe may increase procedural duration slightly, and no concerns about AEs were identified. No data for the impact of CADe/CADx on long-term outcomes, such as interval colorectal cancer (CRC) or mortality, were available. No robust conclusions about effects across different colonoscopy indications or endoscopist experience subgroups could be made.Conclusion The included CADe systems may each increase ADR, with increased detection of other polyp types possible and no major concerns about procedure duration or AEs. Further research on CADx diagnostic accuracy, CADe/CADx impact on long-term outcomes such as CRC incidence and effects across colonoscopy indication and endoscopist experience subgroups is required.PROSPERO registration number CRD42024586541.",
  "authors": [
    {
      "affiliations": [
        "BMJ Technology Assessment Group (BMJ-TAG), BMJ Group, London, England, UK"
      ],
      "name": "Nicole Downes"
    },
    {
      "affiliations": [
        "BMJ Technology Assessment Group (BMJ-TAG), BMJ Group, London, England, UK"
      ],
      "name": "Clare Dadswell"
    },
    {
      "affiliations": [
        "BMJ Technology Assessment Group (BMJ-TAG), BMJ Group, London, England, UK"
      ],
      "name": "Sophie Ip"
    },
    {
      "affiliations": [
        "BMJ Technology Assessment Group (BMJ-TAG), BMJ Group, London, England, UK"
      ],
      "name": "Isaac Mackenzie"
    },
    {
      "affiliations": [
        "BMJ Technology Assessment Group (BMJ-TAG), BMJ Group, London, England, UK"
      ],
      "name": "Victoria Wakefield"
    },
    {
      "affiliations": [
        "BMJ Technology Assessment Group (BMJ-TAG), BMJ Group, London, England, UK"
      ],
      "name": "Steven J Edwards"
    }
  ],
  "title": "Computer-aided polyp detection and characterisation systems to support colonoscopy: a systematic review with results stratified by each individual artificial intelligence system",
  "uid": "8ab72fa4-7b7a-5dd9-8246-ab85df1231c2"
}