Data-driven knowledge acquisition, validation, and transformation into HL7 Arden Syntax
ConclusionData-driven knowledge acquisition and validation against published guidelines were used to help a team of physicians and knowledge engineers create executable clinical knowledge. The advantages of the R-CKM are twofold: it reflects real practices and conforms to standard guidelines, while providing optimal accuracy comparable to that of a PM. The proposed approach yields better insight into the steps of knowledge acquisition and enhances collaboration efforts of the team of physicians and knowledge engineers. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Clinical decision support systems at the Vienna General Hospital using Arden Syntax: Design, implementation, and integration
In this report we take a look at the milestones achieved and the challenges faced in the creation and modification of CDSSs, and their integration into the HIS over the last three years.Materials and methodsWe introduce a three-stage development method, which is followed in nearly all CDSS projects at the Medical University of Vienna and the VGH. Stage one comprises requirements engineering and system conception. Stage two focuses on the implementation and testing of the system. Finally, stage three describes the deployment and integration of the system in the VGH HIS. The HIS provides a clinical work environment for healt...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

User-defined functions in the Arden Syntax: An extension proposal
ConclusionsIt is possible to add user-defined functions to the Arden Syntax in a way that remains coherent with the standard. We believe that this enhances the readability and the robustness of MLMs. A detailed proposal will be submitted by the end of the year to the HL7 workgroup on Arden Syntax. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Transformation of Arden Syntax's medical logic modules into ArdenML for a business rules management system
ConclusionWe have demonstrated that ArdenML can replace a compiler for transforming MLMs into commercial rule engine format. While the proposed XSLT stylesheet requires refinement for general use, we anticipate that the development of further XSLT stylesheets will support various rule engines. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Evolution of the Arden Syntax: Key Technical Issues from the Standards Development Organization Perspective
ConclusionIn response to user demand and to reflect its growing role in clinical decision support, the Arden Syntax has evolved to include a number of powerful features. These depart somewhat from the original vision of the syntax as simple and easily understandable but from the SDO perspective increase the utility of this standard for implementation of CDS. Backwards compatibility has been maintained, allowing continued support of the earlier, simpler decision support models. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Executable medical guidelines with Arden Syntax—Applications in dermatology and obstetrics
DiscussionToday, with the latest versions of Arden Syntax and the application of contemporary software development methods, Arden Syntax has become a powerful and versatile medical knowledge representation and processing language, well suited to implement a large range of CDSSs, including clinical-practice-guideline-based CDSSs. Moreover, such CDS is provided and can be shared as a service by different medical institutions, redefining the sharing of medical knowledge. Arden Syntax is also highly flexible and provides developers the freedom to use up-to-date software design and programming patterns for external patient data...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

How do we talk about doctors and drugs? Sentiment analysis in forums expressing opinions for medical domain
ConclusionsAlthough opinions about physicians and drugs are written in most cases by non-professional users, reviews about physicians are characterized by the use of an informal language while reviews about drugs are characterized by a combination of informal language with specific terminology (e.g. adverse effects, drug names) with greater lexical diversity, making the task of sentiment analysis difficult. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Co-occurrence graphs for word sense disambiguation in the biomedical domain
Publication date: May 2018Source: Artificial Intelligence in Medicine, Volume 87Author(s): Andres Duque, Mark Stevenson, Juan Martinez-Romo, Lourdes AraujoAbstractWord sense disambiguation is a key step for many natural language processing tasks (e.g. summarization, text classification, relation extraction) and presents a challenge to any system that aims to process documents from the biomedical domain. In this paper, we present a new graph-based unsupervised technique to address this problem. The knowledge base used in this work is a graph built with co-occurrence information from medical concepts found in scientific abst...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

A two-step approach for mining patient treatment pathways in administrative healthcare databases
Publication date: May 2018Source: Artificial Intelligence in Medicine, Volume 87Author(s): Ahmed Najjar, Daniel Reinharz, Catherine Girouard, Christian GagnéAbstractClustering electronic medical records allows the discovery of information on healthcare practices. Entries in such medical records are usually composed of a succession of diagnostics or therapeutic steps. The corresponding processes are complex and heterogeneous since they depend on medical knowledge integrating clinical guidelines, the physician's individual experience, and patient data and conditions. To analyze such data, we are first proposing to clu...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: May 2018Source: Artificial Intelligence in Medicine, Volume 87Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Position-aware deep multi-task learning for drug–drug interaction extraction
Publication date: May 2018Source: Artificial Intelligence in Medicine, Volume 87Author(s): Deyu Zhou, Lei Miao, Yulan HeAbstractObjectiveA drug–drug interaction (DDI) is a situation in which a drug affects the activity of another drug synergistically or antagonistically when being administered together. The information of DDIs is crucial for healthcare professionals to prevent adverse drug events. Although some known DDIs can be found in purposely-built databases such as DrugBank, most information is still buried in scientific publications. Therefore, automatically extracting DDIs from biomedical texts is sorely need...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Pharmacological therapy selection of type 2 diabetes based on the SWARA and modified MULTIMOORA methods under a fuzzy environment
Publication date: May 2018Source: Artificial Intelligence in Medicine, Volume 87Author(s): M. Eghbali-Zarch, R. Tavakkoli-Moghaddam, F. Esfahanian, M.M. Sepehri, A. AzaronAbstractMedication selection for Type 2 Diabetes (T2D) is a challenging medical decision-making problem involving multiple medications that can be prescribed to control the patient’s blood glucose. The wide range of hyperglycemia lowering agents with varying effects and various side effects makes the decision quite difficult. This paper presents computer-aided medical decision support using a fuzzy Multi-Criteria Decision-Making (MCDM) model that hy...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Dictionary-based monitoring of premature ventricular contractions: An ultra-low-cost point-of-care service
Publication date: May 2018Source: Artificial Intelligence in Medicine, Volume 87Author(s): S. Chandra Bollepalli, S. Sastry Challa, Laxminarayana Anumandla, Soumya JanaAbstractWhile cardiovascular diseases (CVDs) are prevalent across economic strata, the economically disadvantaged population is disproportionately affected due to the high cost of traditional CVD management, involving consultations, testing and monitoring at medical facilities. Accordingly, developing an ultra-low-cost alternative, affordable even to groups at the bottom of the economic pyramid, has emerged as a societal imperative. Against this backdrop, we...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading
ConclusionWe developed an FS method based on SVM-RFE and AC and successfully showed that its use enabled the identification of the most crucial texture feature of each tissue component. Thus, it makes possible the distinction between multiple Gleason grades (e.g. grade 3 vs. grade 4) and its performance is far superior to other reported FS methods. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification
ConclusionsThe analysis of handwritten dynamics using deep learning techniques showed to be useful for automatic Parkinson's disease identification, as well as it can outperform handcrafted features. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

What matters in a transferable neural network model for relation classification in the biomedical domain?
Publication date: May 2018Source: Artificial Intelligence in Medicine, Volume 87Author(s): Sunil Kumar Sahu, Ashish AnandAbstractA lack of sufficient labeled data often limits the applicability of advanced machine learning algorithms to real life problems. However, the efficient use of transfer learning (TL) has been shown to be very useful across domains. TL make use of valuable knowledge learned in one task (source task), where sufficient data is available, in order to improve performance on the task of interest (target task). In the biomedical and clinical domain, a lack of sufficient training data means that machine le...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning
ConclusionCombining EMKN and MRF is an effective approach for general medical knowledge representation and inference. Different tasks, however, require individually designed energy functions. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

An interoperable clinical decision-support system for early detection of SIRS in pediatric intensive care using openEHR
ConclusionsWe found the use of openEHR Archetypes and AQL a feasible approach to bridge the interoperability gap between local infrastructures and CDSS. The designed concept was successfully transferred into a clinically evaluated openEHR based CDSS. To the authors’ knowledge, this is the first openEHR based CDSS, which is technically reliable and capable in a real context, and facilitates clinical decision-support for a complex task. Further activities will comprise enrichments of the knowledge base, the reasoning processes and cross-institutional evaluations.Graphical abstract (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Extracting cancer mortality statistics from death certificates: A hybrid machine learning and rule-based approach for common and rare cancers
ConclusionThe system proposed in this study provides automatic identification and characterisation of cancers from large collections of free-text death certificates. This allows organisations such as Cancer Registries to monitor and report on cancer mortality in a timely and accurate manner. In addition, the methods and findings are generally applicable beyond cancer classification and to other sources of medical text besides death certificates. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Classifying medical relations in clinical text via convolutional neural networks
This study proposes a convolutional neural network (CNN) architecture with a multi-pooling operation for medical relation classification on clinical records and explores a loss function with a category-level constraint matrix. Experiments using the 2010 i2b2/VA relation corpus demonstrate these models, which do not depend on any external features, outperform previous single-model methods and our best model is competitive with the existing ensemble-based method. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Symptoms and medications change patterns for Parkinson's disease patients stratification
We present two novel approaches. The first algorithm discovers symptoms’ impact on Parkinson's disease progression. Experiments on the Parkinson Progression Markers Initiative (PPMI) data reveal a subset of symptoms influencing disease progression which are already established in Parkinson's disease literature, as well as symptoms that are considered only recently as possible indicators of disease progression by clinicians. The second novelty is a methodology for detecting patterns of medications dosage changes based on the patient status. The methodology combines multitask learning using predictive clustering trees ...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Heart disease diagnosis based on mediative fuzzy logic
Publication date: Available online 30 May 2018Source: Artificial Intelligence in MedicineAuthor(s): Ion IancuAbstractMediative fuzzy logic is an approach able to deal with inconsistent information providing a solution when contradiction exists. The aim of this paper is to design an expert system based on this type of fuzzy logic in order to diagnose a possible heart disease for a patient. Our proposed system is an extension of the standard Mamdani fuzzy logic controller and contains 44 rules of the type single input–single output. The system works with 11 variables as inputs and one variable as output.Graphical abstr...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Segmentation of corneal endothelium images using a U-Net-based convolutional neural network
Publication date: June 2018Source: Artificial Intelligence in Medicine, Volume 88Author(s): Anna FabijańskaAbstractDiagnostic information regarding the health status of the corneal endothelium may be obtained by analyzing the size and the shape of the endothelial cells in specular microscopy images. Prior to the analysis, the endothelial cells need to be extracted from the image. Up to today, this has been performed manually or semi-automatically. Several approaches to automatic segmentation of endothelial cells exist; however, none of them is perfect. Therefore this paper proposes to perform cell segmentation using a U-N...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

MuDeRN: Multi-category classification of breast histopathological image using deep residual networks
ConclusionsMuDeRN can be helpful in the categorization of breast lesions. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

An intelligent algorithm for identification of optimum mix of demographic features for trust in medical centers in Iran
Publication date: June 2018Source: Artificial Intelligence in Medicine, Volume 88Author(s): R. Yazdanparast, S. Abdolhossein Zadeh, D. Dadras, A. AzadehAbstractHealthcare quality is affected by various factors including trust. Patients’ trust to healthcare providers is one of the most important factors for treatment outcomes. The presented study identifies optimum mixture of patient demographic features with respect to trust in three large and busy medical centers in Tehran, Iran. The presented algorithm is composed of adaptive neuro-fuzzy inference system and statistical methods. It is used to deal with data and env...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Lung sounds classification using convolutional neural networks
Publication date: June 2018Source: Artificial Intelligence in Medicine, Volume 88Author(s): Dalal Bardou, Kun Zhang, Sayed Mohammad AhmadAbstractLung sounds convey relevant information related to pulmonary disorders, and to evaluate patients with pulmonary conditions, the physician or the doctor uses the traditional auscultation technique. However, this technique suffers from limitations. For example, if the physician is not well trained, this may lead to a wrong diagnosis. Moreover, lung sounds are non-stationary, complicating the tasks of analysis, recognition, and distinction. This is why developing automatic recognitio...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Leveraging Wikipedia knowledge to classify multilingual biomedical documents
This article presents a classifier that leverages Wikipedia knowledge to represent documents as vectors of concepts weights, and analyses its suitability for classifying biomedical documents written in any language when it is trained only with English documents. We propose the cross-language concept matching technique, which relies on Wikipedia interlanguage links to convert concept vectors between languages. The performance of the classifier is compared to a classifier based on machine translation, and two classifiers based on MetaMap. To perform the experiments, we created two multilingual corpus. The first one, Multi-Li...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Identifying β-thalassemia carriers using a data mining approach: The case of the Gaza Strip, Palestine
Publication date: June 2018Source: Artificial Intelligence in Medicine, Volume 88Author(s): Alaa S. AlAgha, Hossam Faris, Bassam H. Hammo, Ala’ M. Al-ZoubiAbstractThalassemia is considered one of the most common genetic blood disorders that has received excessive attention in the medical research fields worldwide. Under this context, one of the greatest challenges for healthcare professionals is to correctly differentiate normal individuals from asymptomatic thalassemia carriers. Usually, thalassemia diagnosis is based on certain measurable characteristic changes to blood cell counts and related indices. These charac...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: June 2018Source: Artificial Intelligence in Medicine, Volume 88Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards
ConclusionIt is concluded that a patient-centered approach is critical, and that the IoHT paradigm will continue to provide more optimal solutions for patient management in hospital wards.Graphical abstract (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Automatic classification of radiological reports for clinical care
We present in this paper a method based on a cascade of classifiers which make use of a set of syntactic and semantic features. The resulting system is a novel hierarchical classification system for the given task, that we have experimentally evaluated. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

A distance measure between intuitionistic fuzzy sets and its application in medical diagnosis
Publication date: Available online 19 June 2018Source: Artificial Intelligence in MedicineAuthor(s): Minxia Luo, Ruirui ZhaoAbstractThe intuitionistic fuzzy set, as a generation of fuzzy set, can express and process uncertainty much better. Distance measures between intuitionistic fuzzy sets are used to indicate the difference degree between the information carried by intuitionistic fuzzy sets. Although some distance measures have been proposed in previous studies, they can not satisfy the axioms of distance measure, or exist counter-intuitive cases. In this paper, we give a new distance measure between intuitionistic fuzz...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Early anomaly detection in smart home: A causal association rule-based approach
Publication date: Available online 29 June 2018Source: Artificial Intelligence in MedicineAuthor(s): Sfar Hela, Bouzeghoub Amel, Raddaoui BadranAbstractAs the world's population grows older, an increasing number of people are facing health issues. For the elderly, living alone can be difficult and dangerous. Consequently, smart homes are becoming increasingly popular. A sensor-rich environment can be exploited for healthcare applications, in particular, anomaly detection (AD). The literature review for this paper showed that few works consider environmental factors to detect anomalies. Instead, the focus is on user activit...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Decision support system for detection of hypertensive retinopathy using arteriovenous ratio
Publication date: Available online 2 July 2018Source: Artificial Intelligence in MedicineAuthor(s): Shahzad Akbar, Muhammad Usman Akram, Muhammad Sharif, Anam Tariq, Shoab A. KhanAbstractHypertensive Retinopathy (HR) caused by hypertension is a retinal disease which may leads to vision loss and blindness. Computer aided diagnostic systems for various diseases are being used in clinics but there is a need to develop an automated system that detects and grades HR disease. In this paper, an automated system is presented that detects and grades HR disease using Arteriovenous Ratio (AVR).The presented system includes three modu...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Change-point detection method for clinical decision support system rule monitoring
Publication date: Available online 3 July 2018Source: Artificial Intelligence in MedicineAuthor(s): Siqi Liu, Adam Wright, Milos HauskrechtAbstractA clinical decision support system (CDSS) helps clinicians to manage patients, but malfunctions of its components or other systems on which it depends may affect its intended functions. Monitoring the system and detecting changes in its behavior that may indicate the malfunction can help to avoid any potential costs associated with its improper operation. In this paper, we investigate the problem of detecting changes in the CDSS operation, in particular its monitoring and alerti...
Source: Artificial Intelligence in Medicine - July 5, 2018 Category: Bioinformatics Source Type: research

Change-point detection method for clinical decision support system rule monitoring
Publication date: Available online 3 July 2018 Source:Artificial Intelligence in Medicine Author(s): Siqi Liu, Adam Wright, Milos Hauskrecht A clinical decision support system (CDSS) helps clinicians to manage patients, but malfunctions of its components or other systems on which it depends may affect its intended functions. Monitoring the system and detecting changes in its behavior that may indicate the malfunction can help to avoid any potential costs associated with its improper operation. In this paper, we investigate the problem of detecting changes in the CDSS operation, in particular its monitoring and alerting su...
Source: Artificial Intelligence in Medicine - July 3, 2018 Category: Bioinformatics Source Type: research

Decision support system for detection of hypertensive retinopathy using arteriovenous ratio
Publication date: Available online 2 July 2018 Source:Artificial Intelligence in Medicine Author(s): Shahzad Akbar, Muhammad Usman Akram, Muhammad Sharif, Anam Tariq, Shoab A. Khan Hypertensive Retinopathy (HR) caused by hypertension is a retinal disease which may leads to vision loss and blindness. Computer aided diagnostic systems for various diseases are being used in clinics but there is a need to develop an automated system that detects and grades HR disease. In this paper, an automated system is presented that detects and grades HR disease using Arteriovenous Ratio (AVR).The presented system includes three modules i...
Source: Artificial Intelligence in Medicine - July 2, 2018 Category: Bioinformatics Source Type: research

Early anomaly detection in smart home: A causal association rule-based approach
Publication date: Available online 29 June 2018 Source:Artificial Intelligence in Medicine Author(s): Sfar Hela, Bouzeghoub Amel, Raddaoui Badran As the world's population grows older, an increasing number of people are facing health issues. For the elderly, living alone can be difficult and dangerous. Consequently, smart homes are becoming increasingly popular. A sensor-rich environment can be exploited for healthcare applications, in particular, anomaly detection (AD). The literature review for this paper showed that few works consider environmental factors to detect anomalies. Instead, the focus is on user activity and...
Source: Artificial Intelligence in Medicine - June 29, 2018 Category: Bioinformatics Source Type: research

A distance measure between intuitionistic fuzzy sets and its application in medical diagnosis
Publication date: Available online 19 June 2018 Source:Artificial Intelligence in Medicine Author(s): Minxia Luo, Ruirui Zhao The intuitionistic fuzzy set, as a generation of fuzzy set, can express and process uncertainty much better. Distance measures between intuitionistic fuzzy sets are used to indicate the difference degree between the information carried by intuitionistic fuzzy sets. Although some distance measures have been proposed in previous studies, they can not satisfy the axioms of distance measure, or exist counter-intuitive cases. In this paper, we give a new distance measure between intuitionistic fuzzy set...
Source: Artificial Intelligence in Medicine - June 19, 2018 Category: Bioinformatics Source Type: research

Automatic classification of radiological reports for clinical care
We present in this paper a method based on a cascade of classifiers which make use of a set of syntactic and semantic features. The resulting system is a novel hierarchical classification system for the given task, that we have experimentally evaluated. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 7, 2018 Category: Bioinformatics Source Type: research

Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards
Conclusion It is concluded that a patient-centered approach is critical, and that the IoHT paradigm will continue to provide more optimal solutions for patient management in hospital wards. Graphical abstract (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 3, 2018 Category: Bioinformatics Source Type: research

Heart disease diagnosis based on mediative fuzzy logic
Publication date: Available online 30 May 2018 Source:Artificial Intelligence in Medicine Author(s): Ion Iancu Mediative fuzzy logic is an approach able to deal with inconsistent information providing a solution when contradiction exists. The aim of this paper is to design an expert system based on this type of fuzzy logic in order to diagnose a possible heart disease for a patient. Our proposed system is an extension of the standard Mamdani fuzzy logic controller and contains 44 rules of the type single input–single output. The system works with 11 variables as inputs and one variable as output. Graphical abstract ...
Source: Artificial Intelligence in Medicine - May 31, 2018 Category: Bioinformatics Source Type: research

Symptoms and medications change patterns for Parkinson's disease patients stratification
We present two novel approaches. The first algorithm discovers symptoms’ impact on Parkinson's disease progression. Experiments on the Parkinson Progression Markers Initiative (PPMI) data reveal a subset of symptoms influencing disease progression which are already established in Parkinson's disease literature, as well as symptoms that are considered only recently as possible indicators of disease progression by clinicians. The second novelty is a methodology for detecting patterns of medications dosage changes based on the patient status. The methodology combines multitask learning using predictive clustering trees ...
Source: Artificial Intelligence in Medicine - May 24, 2018 Category: Bioinformatics Source Type: research

Classifying medical relations in clinical text via convolutional neural networks
This study proposes a convolutional neural network (CNN) architecture with a multi-pooling operation for medical relation classification on clinical records and explores a loss function with a category-level constraint matrix. Experiments using the 2010 i2b2/VA relation corpus demonstrate these models, which do not depend on any external features, outperform previous single-model methods and our best model is competitive with the existing ensemble-based method. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 19, 2018 Category: Bioinformatics Source Type: research

Extracting cancer mortality statistics from death certificates: A hybrid machine learning and rule-based approach for common and rare cancers
Conclusion The system proposed in this study provides automatic identification and characterisation of cancers from large collections of free-text death certificates. This allows organisations such as Cancer Registries to monitor and report on cancer mortality in a timely and accurate manner. In addition, the methods and findings are generally applicable beyond cancer classification and to other sources of medical text besides death certificates. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 11, 2018 Category: Bioinformatics Source Type: research

An interoperable clinical decision-support system for early detection of SIRS in pediatric intensive care using openEHR
Conclusions We found the use of openEHR Archetypes and AQL a feasible approach to bridge the interoperability gap between local infrastructures and CDSS. The designed concept was successfully transferred into a clinically evaluated openEHR based CDSS. To the authors’ knowledge, this is the first openEHR based CDSS, which is technically reliable and capable in a real context, and facilitates clinical decision-support for a complex task. Further activities will comprise enrichments of the knowledge base, the reasoning processes and cross-institutional evaluations. Graphical abstract (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 10, 2018 Category: Bioinformatics Source Type: research

Identifying β-thalassemia carriers using a data mining approach: The case of the Gaza Strip, Palestine
Publication date: Available online 3 May 2018 Source:Artificial Intelligence in Medicine Author(s): Alaa S. AlAgha, Hossam Faris, Bassam H. Hammo, Ala’ M. Al-Zoubi Thalassemia is considered one of the most common genetic blood disorders that has received excessive attention in the medical research fields worldwide. Under this context, one of the greatest challenges for healthcare professionals is to correctly differentiate normal individuals from asymptomatic thalassemia carriers. Usually, thalassemia diagnosis is based on certain measurable characteristic changes to blood cell counts and related indices. These char...
Source: Artificial Intelligence in Medicine - May 4, 2018 Category: Bioinformatics Source Type: research

Leveraging Wikipedia knowledge to classify multilingual biomedical documents
This article presents a classifier that leverages Wikipedia knowledge to represent documents as vectors of concepts weights, and analyses its suitability for classifying biomedical documents written in any language when it is trained only with English documents. We propose the cross-language concept matching technique, which relies on Wikipedia interlanguage links to convert concept vectors between languages. The performance of the classifier is compared to a classifier based on machine translation, and two classifiers based on MetaMap. To perform the experiments, we created two multilingual corpus. The first one, Multi-Li...
Source: Artificial Intelligence in Medicine - May 4, 2018 Category: Bioinformatics Source Type: research

Lung sounds classification using convolutional neural networks
Publication date: Available online 1 May 2018 Source:Artificial Intelligence in Medicine Author(s): Dalal Bardou, Kun Zhang, Sayed Mohammad Ahmad In recent years, the classification of lung sounds has been the topic of interest in the field of bioinformatics. Lung sounds convey relevant information related to pulmonary disorders, and to evaluate patients with pulmonary conditions, the physician or the doctor uses the traditional auscultation technique. However, this technique suffers from limitations. For example, if the physician is not well trained, this may lead to a wrong diagnosis. Moreover, lung sounds are non-stati...
Source: Artificial Intelligence in Medicine - May 3, 2018 Category: Bioinformatics Source Type: research

An intelligent algorithm for identification of optimum mix of demographic features for trust in medical centers in Iran
Publication date: Available online 26 April 2018 Source:Artificial Intelligence in Medicine Author(s): R. Yazdanparast, S. Abdolhossein Zadeh, D. Dadras, A. Azadeh Healthcare quality is affected by various factors including trust. Patients’ trust to healthcare providers is one of the most important factors for treatment outcomes. The presented study identifies optimum mixture of patient demographic features with respect to trust in three large and busy medical centers in Tehran, Iran. The presented algorithm is composed of adaptive neuro-fuzzy inference system and statistical methods. It is used to deal with data an...
Source: Artificial Intelligence in Medicine - April 26, 2018 Category: Bioinformatics Source Type: research