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The current drug development pipelines are characterised by long processes with high attrition rates and elevated costs. More than 80% of new compounds fail in the later stages of testing due to severe side-effects caused by unknown biomolecular targets of the compounds. In this work, we present a measure that can predict shared targets for drugs in DrugBank through large scale analysis of the biomedical...
Ontology, the shared formal conceptualization of domain information, has been shown to have multiple applications in modeling, processing and understanding natural language text. In this work, we use distributed word vectors out of various recent language models from Deep Learning for semi-automated domain ontology creation for closed domains. We cover all major aspects of Domain Ontology Induction...
Similar diseases are often caused by their similar molecular origins, such as disease-related protein-coding genes (PCGs). And nowadays, the function of PCGs has been widely studied on a gene function network, where each node represents a gene and each edge indicates an interaction between pair-wise genes. Therefore, functional interaction between disease-related PCGs should be exploited to measure...
In order to deal with heterogeneous knowledge in the medical field, this paper proposes a method which can learn a heavy-weighted medical ontology based on medical glossaries and Web resources. Firstly, terms and taxonomic relations are extracted based on disease and drug glossaries and a light-weighted ontology is constructed, Secondly, non-taxonomic relations are automatically learned from Web resources...
As researchers analyze huge amounts of data that are annotated by large biomedical ontologies, one of the major challenges for data mining and machine learning is to leverage both ontologies and data together in a systematic and scalable way. In this paper, we address two interesting and related problems for mining biomedical ontologies and data: i) how to discover semantic associations with the help...
MedReader is a web application that employs the advance of ontology as its knowledgebase. Acting as an online article reader, MedReader benefits non-experts who are interested in reading online medical articles but have trouble comprehending all the technical terminologies appearing therein. In order to help its users mentally grasp the main idea of the article, the reader variegates technical terms...
No SQL stores are emerging as an efficient alternative to relational database management systems in the context of big data. Many actors in this domain consider that to gain a wider adoption, several extensions have to be integrated. Some of them focus on the ways of proposing more schema, supporting adapted declarative query languages and providing integrity constraints in order to control data consistency...
Traditional Chinese Medicine (TCM) has clinical effectives and characteristics in disease diagnosis and treatment, and Chinese Medical Formula and drug therapies. Some new computational techniques and information technologies are needed to manage these large repositories of TCM data and to discover useful patterns and knowledge from them. This study is aimed to present a framework of an ontology based...
This paper presents and analyzes the data requirements within the clinical trial design process with particular focus on the selection of patients who are eligible to participate in the specified clinical study. The latter comprises an extremely time-consuming process which requires considerable budget and effort, whereas the resulting recruited subjects determine both the success of the clinical...
As basic science (ldquobenchrdquo) and medical practice (ldquobedsiderdquo) continue their exponential growth in complexity and scope, the need for finding hidden connections and translating knowledge across disciplines becomes inevitable. The proposed method combines semantic Web technology, graph algorithms, and user profiling to discover and prioritize novel cross-disciplinary associations based...
The WebInVivo project aims at providing automated support for clinical research on neglected diseases. It includes mechanisms for (a) sharing and reusing clinical trial assets, such as protocols, protocol data, workflows and workflow metadata and (b) controlling the protocol life cycle, from modelling to execution. In this project, collaboration in the biomedical area will permeate three segments...
The systematic method used to identify diseases is a called differential diagnosis (DDx). It is mostly used by healthcare professionals to diagnose a specific disease in a patient. If the disease is diagnosed, the method could be used to recommend the medications in order to receive treatment. The goal of the current paper is to design a system based on semantic Web technologies to a system with the...
Despite the excellence of health research done in several countries of different levels of development, it is a reality that few of this research result in new and better drugs and treatments for neglected diseases that affect one-sixth of the world's population. Several reasons contribute for this perverse reality. In this paper we bring to notice that it is not enough to master physical technology...
Health care sector is currently experiencing a major crisis with information overload. With the increasing prevalence of chronic diseases and the ageing population the amount of paper-work is more than ever before. In the US, a hospital admission of one patient generates an estimate of 60 pieces of paper. The federal governments of various countries have passed policies and initiatives that focus...
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