Szczegóły publikacji
Opis bibliograficzny
Artificial intelligence-enabled GRADE: how the GRADE Working Group will use automation to rate the certainty of evidence of intervention effects / Bernardo Sousa-Pinto, Manuel Marques-Cruz, Rafael José Vieira, Vítor Henrique Duarte, Camila Ávila-Oliver, Andreea Dobrescu, Paweł JEMIOŁO, Arnav Agarwal, Małgorzata M. Bała, 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 // Journal of Clinical Epidemiology ; ISSN 0895-4356 . — 2026 — vol. 198 art. no. 112411, s. 1–8. — Bibliogr. s. 8, Abstr. — Publikacja dostępna online od: 2026-07-07. — P. Jemioło - dod. afiliacja: Jagiellonian University Medical College, Krakow, Poland
Autorzy (35)
- Sousa-Pinto Bernardo
- Marques-Cruz Manuel
- Vieira Rafael José
- Duarte Vítor Henrique
- Ávila-Oliver Camila
- Dobrescu Andreea
- AGHJemioło Paweł
- Agarwal Arnav
- Bała Małgorzata Maria
- Beltran Jessica
- Bognanni Antonio
- Cruciani Fabio
- Dawidar Omar
- Gil-Mata Sara
- Liang Changhao
- Martinho-Dias Daniel
- Nowak Claus
- Ocagli Honoria
- Perestrelo Paula
- Pinto Ana Carolina Pereira Nunes
- Reis-Pardal Joana
- Riera-Serra Pau
- Rocha Aline
- Fernández-Saénz Karina
- Etxeandia-Ikobaltzeta Itziar
- Harrou Curtis S.
- Langendam Miranda
- Meerpohl Joerg J.
- Nonino Francesco
- Wiercioch Wojtek
- Neumann Ignacio
- Izcovich Ariel
- Minozzi Silvia
- Gartlehner Gerald
- Schünemann Holger J.
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 169625 |
|---|---|
| Data dodania do BaDAP | 2026-09-26 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.jclinepi.2026.112411 |
| Rok publikacji | 2026 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Journal of Clinical Epidemiology |
Abstract
Objectives The Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group is developing GRADErater (GRADE Rating Automation Through Enhanced Reasoning), an official, automated tool for evaluation of the certainty of evidence (CoE). In this article, we describe the principles and methods underlying its development and state how the GRADE Working Group (GWG) will use automation to rate the CoE of intervention effects. Methods We followed the GRADE methods for registering a project group on GRADE and artificial intelligence (AI). The project group established that the automated tool should be developed according to the following principles: (i) compliance with the current GRADE guidance, (ii) transparency, (iii) human oversight, (iv) implementation of decision rules, (v) ease of use, (vi) understandability, and (vii) continuous improvement. We developed a set of decision rules to appraise each domain of the CoE in pairwise and network meta-analysis. These rules were developed based on official GRADE sources and validated by GRADE experts. Based on these rules, we created a first version ( https://gradeai.med.up.pt/ ) for GRADErater. We are now evaluating this version in terms of (i) its underlying rules and (ii) its user interface. These assessments will allow for a refinement of the rules and of the first version. The modified version will be appraised and presented to the GWG with input from internal and external interest-holders before we seek formal approval. Once launched, the automated tool will be continuously evaluated and refined by incorporating feedback from end users. We will add new features (including generative AI-based functionalities), integrate this tool with GRADEpro, and develop versions in languages other than English. Conclusion This project will follow a transparent methodology to create GRADErater, an official tool endorsed by the GWG that will support humans in applying the most current GRADE methods to rate the CoE.
