Background: Rapid identification of subject experts for medical topics helps in improving the implementation of discoveries by speeding the time to market drugs and aiding in clinical trial recruitment, etc. Identifying such people who influence opinion through social network analysis is gaining prominence. In this work, we explore how to combine named entity recognition from unstructured news articles with social network analysis to discover opinion leaders for a given medical topic.
Methods: We employed a Conditional Random Field algorithm to extract three categories of entities from health-related new articles: Person, Organization and Location. We used the latter two to disambiguate polysemy and synonymy for the person names, used simple rules to identify the subject experts, and then applied social network analysis techniques to discover the opinion leaders among them based on their media presence. A network was created by linking each pair of subject experts who are mentioned together in an article. The social network analysis metrics (including centrality metrics such as Betweenness, Closeness, Degree and Eigenvector) are used for ranking the subject experts based on their power in information flow.
Results: We extracted 734,204 person mentions from 147,528 news articles related to obesity from January 1, 2007 through July 22, 2010. Of these, 147,879 mentions have been marked as subject experts. The F-score of extracting person names is 88.5%. More than 80% of the subject experts who rank among top 20 in at least one of the metrics could be considered as opinion leaders in obesity.
Conclusion: The analysis of the network of subject experts with media presence revealed that an opinion leader might have fewer mentions in the news articles, but a high network centrality measure and vice-versa. Betweenness, Closeness and Degree centrality measures were shown to supplement frequency counts in the task of finding subject experts. Further, opinion leaders missed in scientific publication network analysis could be retrieved from news articles.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3338075 | PMC |
| http://dx.doi.org/10.1186/2041-1480-3-2 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Global metabolomic alterations associated with endocrine-disrupting chemicals among pregnant individuals and newborns.
Metabolomics
January 2025
Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Background: Gestational exposure to non-persistent endocrine-disrupting chemicals (EDCs) may be associated with adverse pregnancy outcomes. While many EDCs affect the endocrine system, their effects on endocrine-related metabolic pathways remain unclear. This study aims to explore the global metabolome changes associated with EDC biomarkers at delivery.
View Article and Find Full Text PDFExplainable vision transformer for automatic visual sleep staging on multimodal PSG signals.
NPJ Digit Med
January 2025
Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea.
Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by the 'black-box' nature. In this study, we present SleepXViT, an automatic sleep staging system using Vision Transformer (ViT) that provides intuitive, consistent explanations by mimicking human 'visual scoring'.
View Article and Find Full Text PDFRIFM fragrance ingredient safety assessment, hexanal, CAS Registry Number 66-25-1.
Food Chem Toxicol
January 2025
Member Expert Panel for Fragrance Safety, The Journal of Dermatological Science (JDS), Department of Dermatology, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu 431-3192, Japan.
Abdominopelvic imaging in the follow-up of testicular germ-cell tumors in adults: recommendations of the Scrotal and Penile Imaging Working Group of the European Society of Urogenital Radiology.
Eur Radiol
January 2025
Department of Radiology, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey.
Objectives: The Scrotal and Penile Imaging Working Group (SPIWG) of the European Society of Urogenital Radiology (ESUR) aimed to formulate recommendations on the imaging modalities and minimal technical requirements for abdominopelvic imaging in the follow-up of adult patients treated for testicular germ-cell tumors (TGCT).
Methods: The SPIWG members performed an extensive literature search, reviewed the current clinical practice, and reached a consensus based on the opinions of experts in the field.
Results: Recurrence in patients treated for TGCT mainly occurs in retroperitoneal lymph nodes (LNs).
Deep learning for forensic age estimation using orthopantomograms in children, adolescents, and young adults.
Eur Radiol
January 2025
Department of Radiology, Jena University Hospital-Friedrich Schiller University, Am Klinikum 1, 07747, Jena, Germany.
Objectives: Forensic age estimation from orthopantomograms (OPGs) can be performed more quickly and accurately using convolutional neural networks (CNNs), making them an ideal extension to standard forensic age estimation methods. This study evaluates improvements in forensic age prediction for children, adolescents, and young adults by training a custom CNN from a previous study, using a larger, diverse dataset with a focus on dental growth features.
Methods: 21,814 OPGs from 13,766 individuals aged 1 to under 25 years were utilized.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!