Jelena Jovanović,Ebrahim Bagheri
Jelena Jovanović
The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical doc...
Large-scale online semantic indexing of biomedical articles via an ensemble of multi-label classification models [0.03%]
基于多标签分类模型集成的大规模在线医学文献语义索引系统
Yannis Papanikolaou,Grigorios Tsoumakas,Manos Laliotis et al.
Yannis Papanikolaou et al.
Background: In this paper we present the approach that we employed to deal with large scale multi-label semantic indexing of biomedical papers. This work was mainly implemented within the context of the BioASQ challenge (...
PIBAS FedSPARQL: a web-based platform for integration and exploration of bioinformatics datasets [0.03%]
PIBAS FedSPARQL：一种用于生物信息数据集集成和探索的网络平台
Marija Djokic-Petrovic,Vladimir Cvjetkovic,Jeremy Yang et al.
Marija Djokic-Petrovic et al.
Background: There are a huge variety of data sources relevant to chemical, biological and pharmacological research, but these data sources are highly siloed and cannot be queried together in a straightforward way. Semanti...
Towards precision medicine: discovering novel gynecological cancer biomarkers and pathways using linked data [0.03%]
迈向精准医疗：利用关联数据发现新的妇科癌症生物标志物和信号通路
Alokkumar Jha,Yasar Khan,Muntazir Mehdi et al.
Alokkumar Jha et al.
Background: Next Generation Sequencing (NGS) is playing a key role in therapeutic decision making for the cancer prognosis and treatment. The NGS technologies are producing a massive amount of sequencing datasets. Often, ...
Towards achieving semantic interoperability of clinical study data with FHIR [0.03%]
使用FHIR实现临床研究数据语义互操作性
Hugo Leroux,Alejandro Metke-Jimenez,Michael J Lawley
Hugo Leroux
Background: Observational clinical studies play a pivotal role in advancing medical knowledge and patient healthcare. To lessen the prohibitive costs of conducting these studies and support evidence-based medicine, result...
Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology [0.03%]
基于本体引导的机器学习方法预测癌症患者的日常生活活动
Hua Min,Hedyeh Mobahi,Katherine Irvin et al.
Hua Min et al.
Background: Bio-ontologies are becoming increasingly important in knowledge representation and in the machine learning (ML) fields. This paper presents a ML approach that incorporates bio-ontologies and its application to...
Design of an extensive information representation scheme for clinical narratives [0.03%]
一种广泛的信息表达方案的临床叙述设计
Louise Deléger,Leonardo Campillos,Anne-Laure Ligozat et al.
Louise Deléger et al.
Background: Knowledge representation frameworks are essential to the understanding of complex biomedical processes, and to the analysis of biomedical texts that describe them. Combined with natural language processing (NL...
Ontology-based specification, identification and analysis of perioperative risks [0.03%]
基于本体的围手术期风险规范、识别与分析
Alexandr Uciteli,Juliane Neumann,Kais Tahar et al.
Alexandr Uciteli et al.
Background: Medical personnel in hospitals often works under great physical and mental strain. In medical decision-making, errors can never be completely ruled out. Several studies have shown that between 50 and 60% of ad...
RDFIO: extending Semantic MediaWiki for interoperable biomedical data management [0.03%]
扩展语义媒体维基以实现生物医学数据管理的互操作性
Samuel Lampa,Egon Willighagen,Pekka Kohonen et al.
Samuel Lampa et al.
Background: Biological sciences are characterised not only by an increasing amount but also the extreme complexity of its data. This stresses the need for efficient ways of integrating these data in a coherent description...
Discovering associations between adverse drug events using pattern structures and ontologies [0.03%]
基于模式结构和本体的药物不良事件间关联的挖掘研究
Gabin Personeni,Emmanuel Bresso,Marie-Dominique Devignes et al.
Gabin Personeni et al.
Background: Patient data, such as electronic health records or adverse event reporting systems, constitute an essential resource for studying Adverse Drug Events (ADEs). We explore an original approach to identify frequen...