Optimizations for Computing Relatedness in Biomedical Heterogeneous Information Networks: SemNet 2.0.

Kirkpatrick, Anna; Onyeze, Chidozie; Kartchner, David; Allegri, Stephen; An, Davi Nakajima; McCoy, Kevin; Davalbhakta, Evie; Mitchell, Cassie S

Kirkpatrick, Anna; Onyeze, Chidozie; Kartchner, David; Allegri, Stephen; An, Davi Nakajima; McCoy, Kevin; Davalbhakta, Evie; Mitchell, Cassie S.

Afiliación

Kirkpatrick A; Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
Onyeze C; School of Mathematics, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Kartchner D; Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
Allegri S; School of Mathematics, Georgia Institute of Technology, Atlanta, GA 30332, USA.
An DN; Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
McCoy K; School of Computer Science, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Davalbhakta E; Laboratory for Pathology Dynamics, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
Mitchell CS; Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.

Big Data Cogn Comput ; 6(1)2022 Mar.

Article en En | MEDLINE | ID: mdl-35936510

Palabras clave

Alzheimer's disease; HeteSim; SemNet; ULARA; biomedical knowledge graph; machine learning; natural language processing; rank aggregation; relatedness; text mining

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Prognostic_studies Idioma: En Revista: Big Data Cogn Comput Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

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