Knowledge graphs, clinical trials, dataspace, and AI: Uniting for progressive healthcare innovation
Timilsina, Mohan Alsamhi, Saeed Haque, Rafiqul Judge, Conor Curry, Edward
Timilsina, Mohan
Alsamhi, Saeed
Haque, Rafiqul
Judge, Conor
Curry, Edward
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Publication Date
2024-01-22
Type
conference paper
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Citation
Timilsina, Mohan, Alsamhi, Saeed, Haque, Rafiqul, Judge, Conor, & Curry, Edward. (2023). Knowledge Graphs, Clinical Trials, Dataspace, and AI: Uniting for Progressive Healthcare Innovation. Paper presented at the 2023 IEEE International Conference on Big Data (BigData), Sorrento, Italy, 15-18 December. 10.1109/BigData59044.2023.10386401
Abstract
Amidst prevailing healthcare challenges, a dynamic solution emerges, fusing knowledge graph technology, clinical tri als optimization, dataspace integration, and AI innovation. This unified approach tackles issues like limited patient insights, sub optimal trial designs, and imprecise treatments. By interlinking diverse data through knowledge graphs, this method illuminates disease trends, therapeutic efficacies, and patient prognoses. AI techniques, especially machine learning, contribute predictive power by unveiling hidden patterns for accurate diagnostics, prognostics, and personalized treatments. This multidisciplinary fusion transforms clinical trials, enhancing comprehensiveness and precision through real-world data analysis and subgroup identification. In reshaping healthcare, this proposition aims to accelerate treatment personalization, elevate therapeutic efficacy, and empower informed medical decisions, encompassing the essence of ’Advancing Healthcare through Innovation: Knowl edge Graphs, Clinical Trials, Dataspace, and AI’.
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Publisher
IEEE
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Attribution 4.0 International