AIMC Topic: Electronic Health Records
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Smoothing dense spaces for improved relation extraction between drugs and adverse reactions.
International journal of medical informatics
May 13, 2019
BACKGROUND AND OBJECTIVE: This work aims at extracting Adverse Drug Reactions (ADRs), i.e. a harm directly caused by a drug at normal doses, from Electronic Health Records (EHRs). The lack of readily available EHRs because of confidentiality issues a...
Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing.
International journal of medical informatics
May 13, 2019
BACKGROUND: The management of hypertrophic cardiomyopathy (HCM) patients requires the knowledge of risk factors associated with sudden cardiac death (SCD). SCD risk factors such as syncope and family history of SCD (FH-SCD) as well as family history ...
A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard.
BMC medical informatics and decision making
May 10, 2019
BACKGROUND: Mobile health (MH) technologies including clinical decision support systems (CDSS) provide an efficient method for patient monitoring and treatment. A mobile CDSS is based on real-time sensor data and historical electronic health record (...
A cross-lingual approach to automatic ICD-10 coding of death certificates by exploring machine translation.
Journal of biomedical informatics
May 8, 2019
Automatic ICD-10 coding is an unresolved challenge in terms of Machine Learning tasks. Despite hospitals generating an enormous amount of clinical documents, data is considerably sparse, associated with a very skewed and unbalanced code distribution,...
Classification of Patients with Coronary Microvascular Dysfunction.
IEEE/ACM transactions on computational biology and bioinformatics
May 2, 2019
While coronary microvascular dysfunction (CMD) is a major cause of ischemia, it is very challenging to diagnose due to lack of CMD-specific screening measures. CMD has been identified as one of the five priority areas of investigation in a 2014 Natio...
Recurrent neural networks with segment attention and entity description for relation extraction from clinical texts.
Artificial intelligence in medicine
May 2, 2019
At present, great progress has been achieved on the relation extraction for clinical texts, but we have noticed that the current models have great drawbacks when dealing with long sentences and multiple entities in a sentence. In this paper, we propo...
Efficient learning from big data for cancer risk modeling: A case study with melanoma.
Computers in biology and medicine
Apr 30, 2019
BACKGROUND: Building cancer risk models from real-world data requires overcoming challenges in data preprocessing, efficient representation, and computational performance. We present a case study of a cloud-based approach to learning from de-identifi...
Predicting coronary artery disease: a comparison between two data mining algorithms.
BMC public health
Apr 29, 2019
BACKGROUND: Cardiovascular diseases (CADs) are the first leading cause of death across the world. World Health Organization has estimated that morality rate caused by heart diseases will mount to 23 million cases by 2030. Hence, the use of data minin...
Extensive phenotype data and machine learning in prediction of mortality in acute coronary syndrome - the MADDEC study.
Annals of medicine
Apr 27, 2019
Investigation of the clinical potential of extensive phenotype data and machine learning (ML) in the prediction of mortality in acute coronary syndrome (ACS). The value of ML and extensive clinical data was analyzed in a retrospective registry stud...
The Price of Artificial Intelligence.
Yearbook of medical informatics
Apr 25, 2019
INTRODUCTION: Whilst general artificial intelligence (AI) is yet to appear, today's narrow AI is already good enough to transform much of healthcare over the next two decades.
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