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Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method.

ABSTRACT: BACKGROUND : Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. We aimed to identify the top implementation research priorities. METHODS : An established modified Delphi approach for research priority setting was used. Fifteen international experts, including endoscopists and translational computer scientists/engineers, from nine countries participated in an online survey over 9 months. Questions related to AI implementation in colonoscopy were generated as a long-list in the first round, and then scored in two subsequent rounds to identify the top 10 research questions. RESULTS : The top 10 ranked questions were categorized into five themes. Theme 1: clinical trial design/end points (4 questions), related to optimum trial designs for polyp detection and characterization, determining the optimal end points for evaluation of AI, and demonstrating impact on interval cancer rates. Theme 2: technological developments (3 questions), including improving detection of more challenging and advanced lesions, reduction of false-positive rates, and minimizing latency. Theme 3: clinical adoption/integration (1 question), concerning the effective combination of detection and characterization into one workflow. Theme 4: data access/annotation (1 question), concerning more efficient or automated data annotation methods to reduce the burden on human experts. Theme 5: regulatory approval (1 question), related to making regulatory approval processes more efficient. CONCLUSIONS : This is the first reported international research priority setting exercise for AI in colonoscopy. The study findings should be used as a framework to guide future research with key stakeholders to accelerate the clinical implementation of AI in endoscopy.

SUBMITTER: Ahmad OF

PROVIDER: S-EPMC8390295 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND: Evidence suggests yoga is a safe and effective intervention for the management of physical and psychosocial symptoms associated with musculoskeletal conditions. However, heterogeneity in the components and reporting of clinical yoga trials impedes both the generalization of study results and the replication of study protocols. The aim of this Delphi survey was to address these issues of heterogeneity, by developing a list of recommendations of key components for the design and reporting of yoga interventions for musculoskeletal conditions. METHODS: Recognised experts involved in the design, conduct, and teaching of yoga for musculoskeletal conditions were identified from a systematic review, and invited to contribute to the Delphi survey. Forty-one of the 58 experts contacted, representing six countries, agreed to participate. A three-round Delphi was conducted via electronic surveys. Round 1 presented an open-ended question, allowing panellists to individually identify components they considered key to the design and reporting of yoga interventions for musculoskeletal conditions. Thematic analysis of Round 1 identified items for quantitative rating in Round 2; items not reaching consensus were forwarded to Round 3 for re-rating. RESULTS: Thirty-six panellists (36/41; 88%) completed the three rounds of the Delphi survey. Panellists provided 348 comments to the Round 1 question. These comments were reduced to 49 items, grouped under five themes, for rating in subsequent rounds. A priori group consensus of ?80% was reached on 28 items related to five themes concerning defining the yoga intervention, types of yoga practices to include in an intervention, delivery of the yoga protocol, domains of outcome measures, and reporting of yoga interventions for musculoskeletal conditions. Additionally, a priori consensus of ?50% was reached on five items relating to minimum values for intervention parameters. CONCLUSIONS: Expert consensus has provided a non-prescriptive reference list for the design and reporting of yoga interventions for musculoskeletal conditions. It is anticipated future research incorporating the Delphi guidelines will facilitate high quality international research in this field, increase homogeneity of intervention components and parameters, and enhance the comparison and reproducibility of research into the use of yoga for the management of musculoskeletal conditions.

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Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method.

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