A Study Protocol for a Comprehensive Evaluation of Two Artificial Intelligence-Based Tools in Title and Abstract Screening for the Development of Evidence-Based Cancer GuidelinesOA
A Study Protocol for a Comprehensive Evaluation of Two Artificial Intelligence-Based Tools in Title and Abstract Screening for the Development of Evidence-Based Cancer Guidelines
Xiaomei Yao;Ashirbani Saha;Sharan Saravanan;Ashley Low;Jonathan Sussman
Department of Health Research Methods,Evidence,and Impact,McMaster University,Hamilton,Ontario,CanadaDepartment of Oncology,McMaster University,Hamilton,Ontario,CanadaDepartment of Oncology,McMaster University,Hamilton,Ontario,CanadaFaculty of Health Sciences,McMaster University,Hamilton,Ontario,CanadaFaculty of Health Sciences,McMaster University,Hamilton,Ontario,Canada
abstract screeningartificial intelligencecancer screeningclinical practice guidelinesDistillerSREPPI-reviewersimulation studysystematic reviewworkload and time savings
abstract screeningartificial intelligencecancer screeningclinical practice guidelinesDistillerSREPPI-reviewersimulation studysystematic reviewworkload and time savings
《肿瘤学创新（英文）》 2025 (4)
96-104,9
This study was supported by the Hamilton Health Sciences Foundation(RD-241).
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