当前位置： SCI文献检索 > JOURNAL OF BIOMEDICAL INFORMATICS期刊下所有文献 > Medical diagnosis of atherosclerosis from Carotid Artery Doppler Signals using principal component analysis (PCA), k-NN based weighting pre-processing and Artificial Immune Recognition System (AIRS).

Medical diagnosis of atherosclerosis from Carotid Artery Doppler Signals using principal component analysis (PCA), k-NN based weighting pre-processing and Artificial Immune Recognition System (AIRS).

Abstract：

:In this study, we proposed a new medical diagnosis system based on principal component analysis (PCA), k-NN based weighting pre-processing, and Artificial Immune Recognition System (AIRS) for diagnosis of atherosclerosis from Carotid Artery Doppler Signals. The suggested system consists of four stages. First, in the feature extraction stage, we have obtained the features related with atherosclerosis disease using Fast Fourier Transformation (FFT) modeling and by calculating of maximum frequency envelope of sonograms. Second, in the dimensionality reduction stage, the 61 features of atherosclerosis disease have been reduced to 4 features using PCA. Third, in the pre-processing stage, we have weighted these 4 features using different values of k in a new weighting scheme based on k-NN based weighting pre-processing. Finally, in the classification stage, AIRS classifier has been used to classify subjects as healthy or having atherosclerosis. Hundred percent of classification accuracy has been obtained by the proposed system using 10-fold cross validation. This success shows that the proposed system is a robust and effective system in diagnosis of atherosclerosis disease.

journal_name

J Biomed Inform

journal_title

Journal of biomedical informatics

authors

Latifoğlu F,Polat K,Kara S,Güneş S

doi

10.1016/j.jbi.2007.04.001

subject

Has Abstract

pub_date

2008-02-01 00:00:00

pages

15-23

issue

1

eissn

1532-0464

issn

1532-0480

pii

S1532-0464(07)00030-5

journal_volume

41

pub_type

杂志文章

相关文献

JOURNAL OF BIOMEDICAL INFORMATICS文献大全
  • Medical speciality classification system based on binary particle swarms and ensemble of one vs. rest support vector machines.

    abstract：:Nowadays, artificial intelligence plays an integral role in medical and healthcare informatics. Developing an automatic question classification and answering system is essential for coping with constant advancements in science and technology. However, efficient online medical services are required to promote offline m...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2020.103525

    authors： Faris H,Habib M,Faris M,Alomari M,Alomari A

    更新日期：2020-09-01 00:00:00

  • Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.

    abstract：:We followed a systematic approach based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) systems that generate structured information from unstructured free text. Seven literature databases were searched with a query combining the...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章,评审

    doi：10.1016/j.jbi.2017.07.012

    authors： Kreimeyer K,Foster M,Pandey A,Arya N,Halford G,Jones SF,Forshee R,Walderhaug M,Botsis T

    更新日期：2017-09-01 00:00:00

  • Characterizing and optimizing human anticancer drug targets based on topological properties in the context of biological pathways.

    abstract：:One of the challenging problems in drug discovery is to identify the novel targets for drugs. Most of the traditional methods for drug targets optimization focused on identifying the particular families of "druggable targets", but ignored their topological properties based on the biological pathways. In this study, we...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2015.02.007

    authors： Zhang J,Wang Y,Shang D,Yu F,Liu W,Zhang Y,Feng C,Wang Q,Xu Y,Liu Y,Bai X,Li X,Li C

    更新日期：2015-04-01 00:00:00

  • Consensus and Meta-analysis regulatory networks for combining multiple microarray gene expression datasets.

    abstract：:Microarray data is a key source of experimental data for modelling gene regulatory interactions from expression levels. With the rapid increase of publicly available microarray data comes the opportunity to produce regulatory network models based on multiple datasets. Such models are potentially more robust with great...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章,meta分析

    doi：10.1016/j.jbi.2008.01.011

    authors： Steele E,Tucker A

    更新日期：2008-12-01 00:00:00

  • Relevance feedback for enhancing content based image retrieval and automatic prediction of semantic image features: Application to bone tumor radiographs.

    abstract：BACKGROUND:The majority of current medical CBIR systems perform retrieval based only on "imaging signatures" generated by extracting pixel-level quantitative features, and only rarely has a feedback mechanism been incorporated to improve retrieval performance. In addition, current medical CBIR approaches do not routine...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2018.07.002

    authors： Banerjee I,Kurtz C,Devorah AE,Do B,Rubin DL,Beaulieu CF

    更新日期：2018-08-01 00:00:00

  • An unsupervised and customizable misspelling generator for mining noisy health-related text sources.

    abstract：BACKGROUND:Data collection and extraction from noisy text sources such as social media typically rely on keyword-based searching/listening. However, health-related terms are often misspelled in such noisy text sources due to their complex morphology, resulting in the exclusion of relevant data for studies. In this pape...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2018.11.007

    authors： Sarker A,Gonzalez-Hernandez G

    更新日期：2018-12-01 00:00:00

  • Explorative data analysis techniques and unsupervised clustering methods to support clinical assessment of Chronic Obstructive Pulmonary Disease (COPD) phenotypes.

    abstract：:Chronic Obstructive Pulmonary Disease (COPD) is the fourth leading cause of death worldwide and represents one of the major causes of chronic morbidity. Cigarette smoking is the most important risk factor for COPD. In these patients, the airflow limitation is caused by a mixture of small airways disease and parenchyma...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2009.05.008

    authors： Paoletti M,Camiciottoli G,Meoni E,Bigazzi F,Cestelli L,Pistolesi M,Marchesi C

    更新日期：2009-12-01 00:00:00

  • A model-driven methodology for exploring complex disease comorbidities applied to autism spectrum disorder and inflammatory bowel disease.

    abstract：:We propose a model-driven methodology aimed to shed light on complex disorders. Our approach enables exploring shared etiologies of comorbid diseases at the molecular pathway level. The method, Comparative Comorbidities Simulation (CCS), uses stochastic Petri net simulation for examining the phenotypic effects of pert...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2016.08.008

    authors： Somekh J,Peleg M,Eran A,Koren I,Feiglin A,Demishtein A,Shiloh R,Heiner M,Kong SW,Elazar Z,Kohane I

    更新日期：2016-10-01 00:00:00

  • Classification models for the prediction of clinicians' information needs.

    abstract：OBJECTIVE:Clinicians face numerous information needs during patient care activities and most of these needs are not met. Infobuttons are information retrieval tools that help clinicians to fulfill their information needs by providing links to on-line health information resources from within an electronic medical record...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2008.07.001

    authors： Del Fiol G,Haug PJ

    更新日期：2009-02-01 00:00:00

  • PharmActa: Personalized pharmaceutical care eHealth platform for patients and pharmacists.

    abstract：:Community pharmacists are critically placed in the patient care chain being an extended frontline within primary healthcare networks across Europe. They are trained to ensure safe and effective medication use, a crucial and responsible role, extending beyond the common misconception limited to just providing timely ac...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2019.103336

    authors： Spanakis M,Sfakianakis S,Kallergis G,Spanakis EG,Sakkalis V

    更新日期：2019-12-01 00:00:00

  • Reflective Random Indexing and indirect inference: a scalable method for discovery of implicit connections.

    abstract：:The discovery of implicit connections between terms that do not occur together in any scientific document underlies the model of literature-based knowledge discovery first proposed by Swanson. Corpus-derived statistical models of semantic distance such as Latent Semantic Analysis (LSA) have been evaluated previously a...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2009.09.003

    authors： Cohen T,Schvaneveldt R,Widdows D

    更新日期：2010-04-01 00:00:00

  • Methodological variations in lagged regression for detecting physiologic drug effects in EHR data.

    abstract：:We studied how lagged linear regression can be used to detect the physiologic effects of drugs from data in the electronic health record (EHR). We systematically examined the effect of methodological variations ((i) time series construction, (ii) temporal parameterization, (iii) intra-subject normalization, (iv) diffe...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2018.08.014

    authors： Levine ME,Albers DJ,Hripcsak G

    更新日期：2018-10-01 00:00:00

  • Automatic signal extraction, prioritizing and filtering approaches in detecting post-marketing cardiovascular events associated with targeted cancer drugs from the FDA Adverse Event Reporting System (FAERS).

    abstract：OBJECTIVE:Targeted drugs dramatically improve the treatment outcomes in cancer patients; however, these innovative drugs are often associated with unexpectedly high cardiovascular toxicity. Currently, cardiovascular safety represents both a challenging issue for drug developers, regulators, researchers, and clinicians ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2013.10.008

    authors： Xu R,Wang Q

    更新日期：2014-02-01 00:00:00

  • Predicting severe clinical events by learning about life-saving actions and outcomes using distant supervision.

    abstract：:Medical error is a leading cause of patient death in the United States. Among the different types of medical errors, harm to patients caused by doctors missing early signs of deterioration is especially challenging to address due to the heterogeneity of patients' physiological patterns. In this study, we implemented r...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2020.103425

    authors： Lee DH,Yetisgen M,Vanderwende L,Horvitz E

    更新日期：2020-07-01 00:00:00

  • Learning classification models from multiple experts.

    abstract：:Building classification models from clinical data using machine learning methods often relies on labeling of patient examples by human experts. Standard machine learning framework assumes the labels are assigned by a homogeneous process. However, in reality the labels may come from multiple experts and it may be diffi...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2013.08.007

    authors： Valizadegan H,Nguyen Q,Hauskrecht M

    更新日期：2013-12-01 00:00:00

  • Benchmarking deep learning models on large healthcare datasets.

    abstract：:Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist which have benchmarked the performance of the deep learning models wit...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2018.04.007

    authors： Purushotham S,Meng C,Che Z,Liu Y

    更新日期：2018-07-01 00:00:00

  • Development of a clinician reputation metric to identify appropriate problem-medication pairs in a crowdsourced knowledge base.

    abstract：BACKGROUND:Correlation of data within electronic health records is necessary for implementation of various clinical decision support functions, including patient summarization. A key type of correlation is linking medications to clinical problems; while some databases of problem-medication links are available, they are...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2013.11.010

    authors： McCoy AB,Wright A,Rogith D,Fathiamini S,Ottenbacher AJ,Sittig DF

    更新日期：2014-04-01 00:00:00

  • The use of logic relationships to model colon cancer gene expression networks with mRNA microarray data.

    abstract：:The ultimate goal of genomics research is to describe the network of molecules and interactions that govern all biological functions and disease processes in cells. Nonlinear interactions among genes in terms of their logic relationships play a key role for deciphering the networks of molecules that underlie cellular ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2007.11.006

    authors： Ruan X,Wang J,Li H,Perozzi RE,Perozzi EF

    更新日期：2008-08-01 00:00:00

  • Combining glass box and black box evaluations in the identification of heart disease risk factors and their temporal relations from clinical records.

    abstract：BACKGROUND:The determination of risk factors and their temporal relations in natural language patient records is a complex task which has been addressed in the i2b2/UTHealth 2014 shared task. In this context, in most systems it was broadly decomposed into two sub-tasks implemented by two components: entity detection, a...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2015.06.014

    authors： Grouin C,Moriceau V,Zweigenbaum P

    更新日期：2015-12-01 00:00:00

  • Feature selection techniques for maximum entropy based biomedical named entity recognition.

    abstract：:Named entity recognition is an extremely important and fundamental task of biomedical text mining. Biomedical named entities include mentions of proteins, genes, DNA, RNA, etc which often have complex structures, but it is challenging to identify and classify such entities. Machine learning methods like CRF, MEMM and ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2008.12.012

    authors： Saha SK,Sarkar S,Mitra P

    更新日期：2009-10-01 00:00:00

  • Annotating longitudinal clinical narratives for de-identification: The 2014 i2b2/UTHealth corpus.

    abstract：:The 2014 i2b2/UTHealth natural language processing shared task featured a track focused on the de-identification of longitudinal medical records. For this track, we de-identified a set of 1304 longitudinal medical records describing 296 patients. This corpus was de-identified under a broad interpretation of the HIPAA ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2015.07.020

    authors： Stubbs A,Uzuner Ö

    更新日期：2015-12-01 00:00:00

  • High-performance implementation and analysis of the Linkmap program.

    abstract：:Linkage analysis uses information from family pedigrees to map genes and locate disease genes on particular chromosomes. A recombination fraction denoted as theta is estimated as a measure of crossing over between two loci. Genetic linkage calculations are very time-consuming particularly for large family pedigrees, a...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1006/jbin.2002.1031

    authors： Kothari K,Lopez-Benitez N,Poduslo SE

    更新日期：2001-12-01 00:00:00

  • A hybrid of whale optimization and late acceptance hill climbing based imputation to enhance classification performance in electronic health records.

    abstract：:Electronic health records (EHR) are a major source of information in biomedical informatics. Yet, missing values are prominent characteristics of EHR. Prediction on dataset with missing values results in inaccurate inferences. Nearest neighbour imputation based on lazy learning approach is a proven technique for missi...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2019.103190

    authors： Nagarajan G,Dhinesh Babu LD

    更新日期：2019-06-01 00:00:00

  • Software tools for simultaneous data visualization and T cell epitopes and disorder prediction in proteins.

    abstract：:We have developed EpDis and MassPred, extendable open source software tools that support bioinformatic research and enable parallel use of different methods for the prediction of T cell epitopes, disorder and disordered binding regions and hydropathy calculation. These tools offer a semi-automated installation of chos...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2016.01.016

    authors： Jandrlić DR,Lazić GM,Mitić NS,Pavlović MD

    更新日期：2016-04-01 00:00:00

  • An evaluation of clinical order patterns machine-learned from clinician cohorts stratified by patient mortality outcomes.

    abstract：OBJECTIVE:Evaluate the quality of clinical order practice patterns machine-learned from clinician cohorts stratified by patient mortality outcomes. MATERIALS AND METHODS:Inpatient electronic health records from 2010 to 2013 were extracted from a tertiary academic hospital. Clinicians (n = 1822) were stratified into lo...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2018.09.005

    authors： Wang JK,Hom J,Balasubramanian S,Schuler A,Shah NH,Goldstein MK,Baiocchi MTM,Chen JH

    更新日期：2018-10-01 00:00:00

  • DEEPEN: A negation detection system for clinical text incorporating dependency relation into NegEx.

    abstract：:In Electronic Health Records (EHRs), much of valuable information regarding patients' conditions is embedded in free text format. Natural language processing (NLP) techniques have been developed to extract clinical information from free text. One challenge faced in clinical NLP is that the meaning of clinical entities...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2015.02.010

    authors： Mehrabi S,Krishnan A,Sohn S,Roch AM,Schmidt H,Kesterson J,Beesley C,Dexter P,Max Schmidt C,Liu H,Palakal M

    更新日期：2015-04-01 00:00:00

  • Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients.

    abstract：BACKGROUND:Allowing patients to access their own electronic health record (EHR) notes through online patient portals has the potential to improve patient-centered care. However, EHR notes contain abundant medical jargon that can be difficult for patients to comprehend. One way to help patients is to reduce information ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2017.02.016

    authors： Chen J,Yu H

    更新日期：2017-04-01 00:00:00

  • A comparison of two methods for retrieving ICD-9-CM data: the effect of using an ontology-based method for handling terminology changes.

    abstract：OBJECTIVE:Most existing controlled terminologies can be characterized as collections of terms, wherein the terms are arranged in a simple list or organized in a hierarchy. These kinds of terminologies are considered useful for standardizing terms and encoding data and are currently used in many existing information sys...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2011.01.005

    authors： Yu AC,Cimino JJ

    更新日期：2011-04-01 00:00:00

  • A method and software framework for enriching private biomedical sources with data from public online repositories.

    abstract：:Modern biomedical research relies on the semantic integration of heterogeneous data sources to find data correlations. Researchers access multiple datasets of disparate origin, and identify elements-e.g. genes, compounds, pathways-that lead to interesting correlations. Normally, they must refer to additional public da...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2016.02.004

    authors： Anguita A,García-Remesal M,Graf N,Maojo V

    更新日期：2016-04-01 00:00:00

  • NCI Thesaurus: a semantic model integrating cancer-related clinical and molecular information.

    abstract：:Over the last 8 years, the National Cancer Institute (NCI) has launched a major effort to integrate molecular and clinical cancer-related information within a unified biomedical informatics framework, with controlled terminology as its foundational layer. The NCI Thesaurus is the reference terminology underpinning the...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2006.02.013

    authors： Sioutos N,de Coronado S,Haber MW,Hartel FW,Shaiu WL,Wright LW

    更新日期：2007-02-01 00:00:00