AIMC Topic: Disease

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What can artificial intelligence teach us about the molecular mechanisms underlying disease?

European journal of nuclear medicine and molecular imaging Jun 12, 2019
While molecular imaging with positron emission tomography or single-photon emission computed tomography already reports on tumour molecular mechanisms on a macroscopic scale, there is increasing evidence that there are multiple additional features wi...
Image Processing, Computer-Assisted Molecular Imaging Disease Humans Artificial Intelligence
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Knowledge-guided convolutional networks for chemical-disease relation extraction.

BMC bioinformatics May 21, 2019
BACKGROUND: Automatic extraction of chemical-disease relations (CDR) from unstructured text is of essential importance for disease treatment and drug development. Meanwhile, biomedical experts have built many highly-structured knowledge bases (KBs), ...
Data Mining Disease Drug-Related Side Effects and Adverse Reactions Knowledge Bases Humans
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Statistical learning approaches in the genetic epidemiology of complex diseases.

Human genetics May 2, 2019
In this paper, we give an overview of methodological issues related to the use of statistical learning approaches when analyzing high-dimensional genetic data. The focus is set on regression models and machine learning algorithms taking genetic varia...
Molecular Epidemiology Disease Algorithms Models, Statistical Artificial Intelligence Humans Machine Learning
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Document-level attention-based BiLSTM-CRF incorporating disease dictionary for disease named entity recognition.

Computers in biology and medicine Apr 7, 2019
BACKGROUND: Disease named entity recognition (NER) plays an important role in biomedical research. There are a significant number of challenging issues to be addressed; among these, the identification of rare diseases and complex disease names and th...
Deep Learning Data Mining Humans Language Terminology as Topic Disease
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Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO.

BMC systems biology Apr 5, 2019
BACKGROUND: Improving efficiency of disease diagnosis based on phenotype ontology is a critical yet challenging research area. Recently, Human Phenotype Ontology (HPO)-based semantic similarity has been affectively and widely used to identify causati...
Humans Phenotype Biological Ontologies Disease
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Deep Collaborative Filtering for Prediction of Disease Genes.

IEEE/ACM transactions on computational biology and bioinformatics Mar 26, 2019
Accurate prioritization of potential disease genes is a fundamental challenge in biomedical research. Various algorithms have been developed to solve such problems. Inductive Matrix Completion (IMC) is one of the most reliable models for its well-est...
Humans Algorithms Deep Learning Mice Animals Genes Databases, Genetic Disease Genetic Association Studies Computational Biology
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PMAMCA: prediction of microRNA-disease association utilizing a matrix completion approach.

BMC systems biology Mar 20, 2019
BACKGROUND: Numerous experimental results have indicated that microRNAs (miRNAs) play a vital role in biological processes, as well as outbreaks of diseases at the molecular level. Despite their important role in biological processes, knowledge regar...
MicroRNAs Disease Humans Computational Biology Databases, Genetic Machine Learning
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Automated Closed- and Open-Loop Validation of Knowledge-Based Planning Routines Across Multiple Disease Sites.

Practical radiation oncology Mar 1, 2019
PURPOSE: Knowledge-based planning (KBP) clinical implementation necessitates significant upfront effort, even within a single disease site. The purpose of this study was to demonstrate an efficient method for clinicians to assess the noninferiority o...
Male Knowledge Bases Radiotherapy, Intensity-Modulated Disease Validation Studies as Topic Humans Retrospective Studies
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Mining Disease-Symptom Relation from Massive Biomedical Literature and Its Application in Severe Disease Diagnosis.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Disease-symptom relation is an important biomedical relation that can be used for clinical decision support including building medical diagnostic systems. Here we present a study on mining disease-symptom relation from massive biomedical literature a...
Symptom Assessment Information Storage and Retrieval PubMed Disease MEDLINE Biological Ontologies Data Mining Diagnosis Humans Decision Support Systems, Clinical
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relSCAN - A system for extracting chemical-induced disease relation from biomedical literature.

Journal of biomedical informatics Oct 6, 2018
This paper proposes an effective and robust approach for Chemical-Induced Disease (CID) relation extraction from PubMed articles. The study was performed on the Chemical Disease Relation (CDR) task of BioCreative V track-3 corpus. The proposed system...
Disease Machine Learning Chemically-Induced Disorders Algorithms Medical Informatics Humans Random Allocation Support Vector Machine Publications Regression Analysis Decision Making Data Mining
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