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find Author "YAN Yilong" 2 results
  • Evidence intelligent synthesis and grading: development and validation of AutoMeta

    AutoMeta is a semi-automated, interactive, user-friendly online platform developed by Chinese scholars with independent intellectual property rights. This platform is designed to assist users in completing pairwise meta-analysis, inverse variance meta-analysis, network meta-analysis, and diagnostic test accuracy meta-analysis and use the GRADE method to achieve automatic grading of certainty of evidence. Nowadays, the AutoMeta platform can conduct the pairwise meta-analysis and inverse variance meta-analysis, as well as the automatic grading of certainty of evidence for pairwise meta-analysis. This article introduces the platform to users in terms of its development techniques, operation methods and verification of the accuracy of results, aiming to assist researchers to conduct systematic reviews quickly.

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  • Report and quality analysis of health technology assessment

    Objective To investigate the health technology assessment reports, analyze publication characteristics and report quality, and explore hot topics in health technology assessment. Methods Web of Science and CNKI databases were searched to collect complete health technology assessment reports from inception to January 2023. SPSS 26.0 software was used to analyze the publication journals, countries, number of authors, assessment types and assessment contents of the assessment reports. The report quality was assessed based on International Network of Agencies for Health Technology Assessment (INAHTA) report criteria (2007 edition). VOSviewer 1.6.11 was used to analyze keywords clustering. Results A total of 216 papers were included, with 158 published by Chinese authors, and a rapid growth trend in the number of reports over past four years. The rate of reports on health technology social adaptability assessment was only 17.13%. Among the Chinese reports, 25 were general health technology assessments, 35 were rapid assessments, and 3 were mini assessments. Among the English reports, 4 were rapid assessments, and 54 were regular healthcare technology assessments. For the 14 items in the INAHTA reporting criteria, the reporting rates were high for the brief summary (98.61%), problem description (94.91%), and results discussion entries (97.69%). However, the reporting rates were low for criteria such as personnel responsibilities, conflict of interest statements, and peer review statements, at 31.94%, 19.44%, and 3.24% respectively. English literature generally exhibited higher report quality. Conclusion In recent years, the volume of health technology assessment reports in China has been increasing, with developments in assessment types and application fields. However, there are also problems with standardization of reporting.

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