Quantitative analysis of artificial intelligence on liver cancer: A bibliometric analysis

Update report on the quality of gliomas radiomics: An integration of bibliometric and radiomics quality score

BACKGROUND

Despite the increasing number of publications on glioma radiomics, challenges persist in clinical translation.

AIM

To assess the development and reporting quality of radiomics in brain gliomas since 2019.

METHODS

A bibliometric analysis was conducted to reveal trends in brain glioma radiomics research. The Radiomics Quality Score (RQS), a metric for evaluating the quality of radiomics studies, was applied to assess the quality of adult-type diffuse glioma studies published since 2019. The total RQS score and the basic adherence rate for each item were calculated. Subgroup analysis by journal type and research objective was performed, correlating the total RQS score with journal impact factors.

RESULTS

The radiomics research in glioma was initiated in 2011 and has witnessed a surge since 2019. Among the 260 original studies, the median RQS score was 11, correlating with a basic compliance rate of 46.8%. Subgroup analysis revealed significant differences in domain 1 and its subitems (multiple segmentations) across journal types (P = 0.039 and P = 0.03, respectively). The Spearman correlation coefficients indicated that the total RQS score had a negative correlation with the Journal Citation Report category (-0.69) and a positive correlation with the five-year impact factors (0.318) of journals.

CONCLUSION

Glioma radiomics research quality has improved since 2019 but necessitates further advancement with higher publication standards.

Bibliometric analysis and research trends of artificial intelligence in lung cancer

Background

Due to the rapid advancement of technology, artificial intelligence (AI) has become extensively used for the diagnosis and prognosis of various diseases, such as lung cancer. Research in the field of literature has demonstrated that artificial intelligence (AI) can be valuable in the timely detection of lung cancer and the formulation of an effective treatment plan. This study aims to conduct a bibliometric analysis to examine and illustrate the specific areas of focus, research frontiers, evolutionary processes, and trends in existing research on artificial intelligence in the context of lung cancer.

Methods

Publications on AI in lung cancer were selected from the SCIE and ESCI indexes on September 19, 2023. The examination of nations, academic publications, organizations, writers, citations, and terms in this domain was visually analyzed with InCites and VOSviewer.

Results

In this study, a total of 4275 publications were selected and analyzed. Artificial intelligence-related lung cancer publications have increased significantly in the last 5 years. China and the USA have contributed the most to the literature in this field (1418 publications with 13.92 citation impacts and 1117 publications with 37.34 citation impacts, respectively). The institution with the highest contribution was "Chinese Academy of Sciences," with 118 publications and 29.09 citation impacts. Among the research categories, "Radiology, Nuclear Medicine & Imaging", "Oncology", and "Engineering, Biomedical" were in first place.

Conclusion

The USA and China have always been leaders in this field and will continue to be for some time. Research in countries such as the Netherlands is increasing. However, research collaboration has to be strengthened in developing countries.

Indexing blood banking performance in India: A retrospective cross-sectional analysis of states and districts

Background

Multiple international assessments have highlighted gaps in blood banking globally. However, there is a dearth of subnational assessments. We applied a thematic framework with multiple composite indices to assess blood bank performance across Indian states and districts.

Methods

In this retrospective cross-sectional analysis, data for 2493 blood banks in 35 states/union territories (UTs) and 616 districts was extracted from the National Blood Transfusion Council for 2016. The framework involved seven themes (accreditation, ownership, safety, volume, infrastructure, regulation, and workforce) with several indicators nested under them. Composite thematic indices and an overall index (0-100, with 100 being the best performance) were constructed using the adjusted Mazziotta-Pareto index method that can provide composite indices that are partially non-compensatory and easily interpretable.

Results

The state-level median [interquartile range] value of the overall index was 59.61 [46.35, 71.67]. Chandigarh had the highest values for safety, regulation, workforce, and ownership indices, Maharashtra for volume and infrastructure indices, and Manipur for accreditation index. Districts in southern and western states performed well on the overall index with inter- and intra-state variations for themes. District-level correlations depicted positive associations among indices with the strongest correlation between ownership and accreditation indices (n=616, R=0.92, p<0.001).

Conclusion

Blood banking in India is fragmented, with variations in themes across geographies. The northern and northeastern states require more attention for volume, accreditation, infrastructure, and ownership. While the southern and western-central regions need to prioritize safety. The framework with thematic indices, when applied to routine data, can be useful for monitoring and evaluation to decide local policies and resource allocations.