{"id":16,"date":"2024-02-21T16:14:48","date_gmt":"2024-02-21T16:14:48","guid":{"rendered":"http:\/\/socio.org.uk\/ddp\/?page_id=16"},"modified":"2024-08-21T05:18:17","modified_gmt":"2024-08-21T05:18:17","slug":"workshop","status":"publish","type":"page","link":"https:\/\/socio.org.uk\/ddp2024\/workshop\/","title":{"rendered":"Workshop"},"content":{"rendered":"

Data Analytics in Biomedicine<\/span><\/h1>\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n

held in conjunction with IEEE<\/span>\u00a0<\/span>DDP2024<\/span><\/a>\u00a0<\/span><\/span><\/p>\n

New York, US<\/span><\/p>\n

30 September – 01 October 2024<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n

\n
<\/div>\n
\n
\n
\n
\n
\n
\n
\n
\n
\n

CALL FOR PAPERS<\/span><\/strong><\/span><\/p>\n

The exponential growth of data generated from various textual sources presents both a challenge and a huge opportunity. A key challenge lies in effectively managing and extracting valuable insights from this vast amount of unstructured and heterogeneous data. To address this issue, advanced data analytics techniques ranging from data and text mining to semantic network analysis, as well as the recent advancements in large language models (LLMs) have become indispensable tools for researchers and practitioners.<\/span><\/p>\n

This is particularly relevant in the realm of biomedicine, where text mining has shown the ability to enable researchers to uncover hidden patterns, trends, and associations that would otherwise remain buried in the vast amount of health-related textual data, as for instance research articles, clinical reports, and electronic health records (EHRs).<\/span><\/p>\n

On the other hand, semantic network analysis that focus on understanding the structure and dynamics of networks formed by the entities and their interconnections derived from text mining processes, can facilitate a deeper understanding of the complex interrelationships within biomedical data. By analyzing properties like centrality, modularity, and community structures, researchers can identify key nodes and critical pathways in biological networks, predict disease associations, and explore the functional organization of biological systems.<\/span><\/p>\n

The integration of text mining, semantic network analysis, and large language models offers a powerful approach not only to enhance the ability to generate new hypotheses and insights but also to support the development of more effective diagnostics, treatments, and interventions<\/span><\/p>\n

The workshop represents an opportunity to explore the latest advancements in data analytics and text mining applied to biomedicine. Attendees will gain insights into developing more interpretable models, handling large-scale biomedical datasets, and implementing scalable solutions for real-world healthcare applications.<\/span><\/p>\n

Moreover, the workshop is highly relevant due to its potential to significantly improve the safety, effectiveness, and efficiency of biomedical interventions through advanced data analytics.<\/span><\/p>\n

TOPIC OF INTEREST<\/span><\/strong><\/span><\/p>\n

We invite submissions on a wide range of topics, including but not limited to:<\/span><\/p>\n