A novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviews-Reference-Cited by-同舟云学术

A novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviews

Published:2023-03 Issue: Volume:6 Page:100162
ISSN:2772-6622
Container-title:Decision Analytics Journal
language:en
Short-container-title:Decision Analytics Journal

Author:

Moreno-Garcia Carlos Francisco^ORCID,Jayne Chrisina^ORCID,Elyan Eyad^ORCID,Aceves-Martins Magaly^ORCID

Publisher

Elsevier BV

Subject

Modeling and Simulation,Applied Mathematics,Analysis,General Decision Sciences

Reference51 articles.

1. (Semi)automated approaches to data extraction for systematic reviews and meta-analyses in social sciences: A living review protocol [version 1; peer review: 3 approved with reservations] 11:1036;Legate,2022

2. A step by step guide for conducting a systematic review and meta-analysis with simulation data;Tawfik,2019

3. Interventions to Treat Obesity in Mexican Children and Adolescents: Systematic Review and Meta-Analysis;Aceves-Martins;Nutr. Rev.,2021

4. Reducing workload in systematic review preparation using automated citation classification, 13 (2);Cohen,2006

5. Recent advances in clinical natural language processing in support of semantic analysis, 24 (01);Mowery,2015

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automated Paper Screening for Clinical Reviews Using Large Language Models: Data Analysis Study;Journal of Medical Internet Research;2024-01-12

2. A Zero-Shot Interpretable Framework for Sentiment Polarity Extraction;IEEE Access;2024

3. A Novel Question-Answering Framework for Automated Citation Screening Using Large Language Models;2023-12-18

4. Sensitivity, specificity and avoidable workload of using a large language models for title and abstract screening in systematic reviews and meta-analyses;2023-12-17

5. New boosting approaches for improving cluster-based undersampling in problems with imbalanced data;Decision Analytics Journal;2023-09