Khám Phá Mẫu Từ Các Mối Quan Hệ Tương Tác Thuốc - Thuốc Cấp Cao

Journal of Healthcare Informatics Research - Tập 2 - Trang 272-304 - 2018
Wen-Hao Chiang1, Titus Schleyer2, Li Shen3, Lang Li4, Xia Ning1,5
1Department of Computer & Information Science, Indiana University - Purdue University Indianapolis, Indianapolis, USA
2Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, USA
3Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Pennsylvania, USA
4Department of Biomedical Informatics, The Ohio State University, Columbus, USA
5Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, USA

Tóm tắt

Các tương tác thuốc - thuốc (DDIs) và các phản ứng có hại liên quan đến thuốc (ADRs) đại diện cho một vấn đề sức khỏe cộng đồng quan trọng tại Hoa Kỳ. Nghiên cứu được trình bày trong bản thảo này giải quyết các vấn đề liên quan đến việc biểu diễn, định lượng, phát hiện và trực quan hóa các mẫu từ các DDI cấp cao theo cách hoàn toàn dựa trên dữ liệu trong một khuôn khổ dựa trên đồ thị thống nhất và thông qua các thuật toán tích chập thống nhất. Chúng tôi xác định vấn đề dựa trên các khái niệm về quan hệ DDI không định hướng (DDI-nd) và quan hệ DDI định hướng (DDI-d), và tương ứng phát triển các đồ thị hoàn chỉnh được trọng số và các siêu đồ thị cho việc biểu diễn của chúng. Chúng tôi cũng phát triển một sơ đồ tích chập và thuật toán ngẫu nhiên của nó $\text {SD}^{2}\text {ID}^{2}\text {S}$ để khám phá sự tương đồng giữa các loại thuốc dựa trên DDI. Kết quả thực nghiệm của chúng tôi cho thấy các phương pháp như vậy có thể nắm bắt tốt các mẫu của các DDI cấp cao.

Từ khóa

#tương tác thuốc #phản ứng có hại #thuật toán ngẫu nhiên #đồ thị #trực quan hóa dữ liệu #kiểu hình thuốc

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