AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Data Warehousing

Showing 1 to 10 of 13 articles

Clear Filters

Metadata Import from RDF to i2b2.

Studies in health technology and informatics
Metadata management is an important task in medical informatics and highly affects the gain out of existing health information data. Data Warehouse solutions like Informatics for Integrating Biology and the Bedside (i2b2) are common tools for identif...

Provenance for Biomedical Ontologies with RDF and Git.

Studies in health technology and informatics
The German Center for Lung Research (DZL) is a research network with the aim of researching respiratory diseases. In order to enable consortium-wide retrospective research and prospective patient recruitment, we perform data integration into a centra...

Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach.

Journal of Korean medical science
BACKGROUND: Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a severe mismatch reaction, and the result can also support the diagnosis of various disease or prediction of drug side effects. However, such secondary ...

Prescreening in Oncology Using Data Sciences: The PreScIOUS Study.

Studies in health technology and informatics
The development of precision medicine in oncology to define profiles of patients who could benefit from specific and relevant anti-cancer therapies is essential. An increasing number of specific eligibility criteria are necessary to be eligible to ta...

The Challenges of Implementing Comprehensive Clinical Data Warehouses in Hospitals.

International journal of environmental research and public health
Digital health, e-health, telemedicine-this abundance of terms illustrates the scientific and technical revolution at work, made possible by high-speed processing of health data, artificial intelligence (AI), and the profound upheavals currently taki...

FHIR-Ontop-OMOP: Building clinical knowledge graphs in FHIR RDF with the OMOP Common data Model.

Journal of biomedical informatics
BACKGROUND: Knowledge graphs (KGs) play a key role to enable explainable artificial intelligence (AI) applications in healthcare. Constructing clinical knowledge graphs (CKGs) against heterogeneous electronic health records (EHRs) has been desired by...

Deep learning approach to detection of colonoscopic information from unstructured reports.

BMC medical informatics and decision making
BACKGROUND: Colorectal cancer is a leading cause of cancer deaths. Several screening tests, such as colonoscopy, can be used to find polyps or colorectal cancer. Colonoscopy reports are often written in unstructured narrative text. The information em...

Development and Validation of a Natural Language Processing Algorithm to Pseudonymize Documents in the Context of a Clinical Data Warehouse.

Methods of information in medicine
OBJECTIVE: The objective of this study is to address the critical issue of deidentification of clinical reports to allow access to data for research purposes, while ensuring patient privacy. The study highlights the difficulties faced in sharing tool...

Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop and validate a natural language processing (NLP) pipeline that detects 18 conditions in French clinical notes, including 16 comorbidities of the Charlson index, while exploring a collaborative and privacy-enhancing workflow.