A scoping review of semantic integration of health data and information

H Zhang, T Lyu, P Yin, S Bost, X He, Y Guo… - International Journal of …, 2022 - Elsevier
Objective We summarized a decade of new research focusing on semantic data integration
(SDI) since 2009, and we aim to:(1) summarize the state-of-art approaches on integrating …

Trends and features of the applications of natural language processing techniques for clinical trials text analysis

X Chen, H Xie, G Cheng, LKM Poon, M Leng… - Applied Sciences, 2020 - mdpi.com
Natural language processing (NLP) is an effective tool for generating structured information
from unstructured data, the one that is commonly found in clinical trial texts. Such …

As ontologies reach maturity, artificial intelligence starts being fully efficient: findings from the section on knowledge representation and management for the yearbook …

F Dhombres, J Charlet - Yearbook of medical informatics, 2018 - thieme-connect.com
Objectives: To select, present, and summarize the best papers published in 2017 in the field
of Knowledge Representation and Management (KRM). Methods: A comprehensive and …

An ontology-based documentation of data discovery and integration process in cancer outcomes research

H Zhang, Y Guo, M Prosperi, J Bian - BMC Medical Informatics and …, 2020 - Springer
Background To reduce cancer mortality and improve cancer outcomes, it is critical to
understand the various cancer risk factors (RFs) across different domains (eg, genetic …

Differential gene expression analysis of RNA-seq data using machine learning for Cancer research

J Liñares Blanco, M Gestal, J Dorado… - … : applications of learning …, 2019 - Springer
Transcriptome analysis, as a tool for the characterization and understanding of phenotypic
alterations in molecular biology, plays an integral role in the understanding of complex, multi …

Knowledge guided integration of structured and unstructured data in health decision process

M Radaoui, S Ben Abdallah Ben Lamine… - 2019 - aisel.aisnet.org
Data in the health domain is continuously increasing. It is collected from several sources,
has several formats and is characterized by its sensibility (protection of personal health …

Histogram distance metric learning to diagnose breast cancer using semantic analysis and natural language interpretation methods

DG Jebadas, M Sivaram, BS Vidhyasagar… - … and advancements of …, 2022 - Springer
Breast cancer is one of the major causes of mortality rate increase among women, in both
developed and under-developed countries. Hormone-dependent cancers are possibly …

Cancer precision medicine today: Towards omic information in healthcare systems

N Maggi, R Gazzarata, C Ruggiero… - Tumori …, 2019 - journals.sagepub.com
Introduction: This article focuses on the integration of omics data in electronic health records
and on interoperability aspects relating to big data analysis for precision medicine. Methods …

Enhancing Predictive Power in Personalized Breast Cancer Treatment through the Integration of Multi-Omics Data and Clinical Information with Deep Learning …

A Varpe, R Bhujbal, R Kumar - 2024 MIT Art, Design and …, 2024 - ieeexplore.ieee.org
The paper explores the complexities of personalized breast cancer treatment, by integration
of multi-omics data, clinical data, and advanced computational tools. The heterogeneous …

Using semantic web technologies to underpin the SNOMED CT query language

MA Casteleiro, D Tsarkov, B Parsia… - Artificial Intelligence XXXIV …, 2017 - Springer
SNOMED International is working on a query language specification for SNOMED CT, which
we call here SCTQL. SNOMED CT is the leading terminology for use in Electronic Health …