Artificial Intelligence-enabled GRADE: how the GRADE Working Group will use automation to rate the certainty of evidence of intervention effects
Year: 2026
Type: article
Source: Journal of Clinical Epidemiology
Authors: Bernardo Sousa-Pinto, Manuel Marques-Cruz, Rafael José Vieira, Vítor Henrique Duarte, Camila Ávila-Oliver, Andreea Dobrescu, Paweł Jemioło, Arnav Agarwal, Malgorzata M. Bala, Jessica Beltran, Antonio Bognanni, Fabio Cruciani, Omar Dewidar, Sara Gil-Mata, Changhao Liang, Daniel Martinho-Dias, Claus Nowak, Honoria Ocagli, Paula Perestrelo, Ana Carolina Pereira Nunes Pinto, Joana Reis-Pardal, Pau Riera-Serra, Aline Rocha, Karina Fernández-Saénz, Itziar Etxeandia-Ikobaltzeta, Curtis S. Harrod, Miranda W. Langendam, Joerg Meerpohl, Francesco Nonino, Wojtek Wiercioch, Ignacio Neumann, Ariel Izcovich, Silvia Minozzi, Gerald Gartlehner, Holger J. Schünemann
Institutions: Universidade do Porto, Centre for Health Technology and Services Research, RISE - Health Research Network, Universidad del Desarrollo, Clínica Alemana, Universität für Weiterbildung Krems, Jagiellonian University, AGH University of Krakow, University of Alberta, Iberoamerican Cochrane Centre, Institut de Recerca Sant Pau, Humanitas University, ASL Roma, University of Ottawa, University of Toronto, Bruyere Health Research Institute, Beijing University of Chinese Medicine, McMaster University, University of Padua, Health Research Institute of the Balearic Islands, Cochrane, Universidade Federal de São Paulo, American College of Physicians, Amsterdam Public Health, Amsterdam University Medical Centers, University of Amsterdam, University of Freiburg, Cochrane Deutschland Stiftung, Cochrane, Istituto delle Scienze Neurologiche di Bologna, Cochrane Canada, Universidad San Sebastián, Universidad del Salvador, Hospital Alemán, Mario Negri Institute for Pharmacological Research, RTI International, Charité – Universitätsmedizin Berlin
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7167636727