Forecasting emerging trends in transfusion medicine through complex network analysis of scholars' research.
Аннотация
BACKGROUND AND
OBJECTIVES
This study aimed to analyse and predict emerging trends in transfusion medicine using complex network analysis of high-impact global scholar rankings.
MATERIALS AND
METHODS
Network analysis was employed to uncover research trends, identify central research directions and map knowledge networks. The analytical hierarchy process was used to evaluate potential future research trajectories. The Kolmogorov-Smirnov test assessed network centrality differences, with cross-validation performed using the Association for the Advancement of Blood & Biotherapies (AABB) and the International Society of Blood Transfusion (ISBT) conference themes.
RESULTS
Clinical transfusion is the central theme, with transfusion management, evaluation and specific transfusions like platelet and plasma gaining prominence. Blood safety evolved into a standalone domain, while immunohaematology and cell therapy represent emerging trends. Innovations in blood storage, transfusion technology and omics insights are shaping future directions. Notably, despite global healthcare impacts, COVID-19 has not significantly redirected transfusion medicine research.
CONCLUSION
The transfusion medicine landscape demonstrates stability in its core framework while increasingly focusing on emerging areas such as personalized therapies, platelet transfusion and cell-based treatments.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.