Related papers: Ontology Based Information Extraction for Disease …
The healthcare environment is commonly referred to as "information-rich" but also "knowledge poor". Healthcare systems collect huge amounts of data from various sources: lab reports, medical letters, logs of medical tools or programs,…
Health informatics can inform decisions that practitioners, patients, policymakers, and researchers need to make about health and disease. Health informatics is built upon patient health data leading to the need to codify patient health…
The work presented in this master thesis consists of extracting a set of events from texts written in natural language. For this purpose, we have based ourselves on the basic notions of the information extraction as well as the open…
Modern epidemiology integrates knowledge from heterogeneous collections of data consisting of numerical, descriptive and imaging. Large-scale epidemiological studies use sophisticated statistical analysis, mathematical models using…
Artificial Intelligence (AI) technology is based on theory and development of computer systems able to perform tasks that normally require human intelligence. In this context, deep learning is a family of computational methods that allow an…
Stratifying cancer patients based on their gene expression levels allows improving diagnosis, survival analysis and treatment planning. However, such data is extremely highly dimensional as it contains expression values for over 20000 genes…
With the advancements in computer technology, there is a rapid development of intelligent systems to understand the complex relationships in data to make predictions and classifications. Artificail Intelligence based framework is rapidly…
Worldwide, several cases go undiagnosed due to poor healthcare support in remote areas. In this context, a centralized system is needed for effective monitoring and analysis of the medical records. A web-based patient diagnostic system is a…
Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations…
Anonymized electronic medical records are an increasingly popular source of research data. However, these datasets often lack race and ethnicity information. This creates problems for researchers modeling human disease, as race and…
Software testing is a prime factor in software industry. Besides knowing the importance of testing, only limited time is allocated for teaching it. It will be more efficient if testing is taught simultaneously with programming foundations.…
Infectious diseases remain a critical global health challenge, and the integration of standardized ontologies plays a vital role in managing related data. The Infectious Disease Ontology (IDO) and its extensions, such as the Coronavirus…
In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the…
Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within…
Nowadays, a huge amount of knowledge has been amassed in digital agriculture. This knowledge and know-how information are collected from various sources, hence the question is how to organise this knowledge so that it can be efficiently…
Epistemic AI accelerates biomedical discovery by finding hidden connections in the network of biomedical knowledge. The Epistemic AI web-based software platform embodies the concept of knowledge mapping, an interactive process that relies…
While previous studies have demonstrated the potential of AI to diagnose diseases in imaging data, clinical implementation is still lagging behind. This is partly because AI models require training with large numbers of examples only…
The upcoming technology support for semantic web promises fresh directions for Software Engineering community. Also semantic web has its roots in knowledge engineering that provoke software engineers to look for application of ontology…
Here we understand 'intelligence' as referring to items of knowledge collected for the sake of assessing and maintaining national security. The intelligence community (IC) of the United States (US) is a community of organizations that…
Gene Ontology (GO) is the most important resource for gene function annotation. It provides a way to unify biological knowledge across different species via a dynamic and controlled vocabulary. GO is now widely represented in the Semantic…