当前位置： SCI文献检索 > JOURNAL OF BIOMEDICAL INFORMATICS期刊下所有文献 > Induction of comprehensible models for gene expression datasets by subgroup discovery methodology.

Induction of comprehensible models for gene expression datasets by subgroup discovery methodology.

Abstract：

:Finding disease markers (classifiers) from gene expression data by machine learning algorithms is characterized by a high risk of overfitting the data due the abundance of attributes (simultaneously measured gene expression values) and shortage of available examples (observations). To avoid this pitfall and achieve predictor robustness, state-of-the-art approaches construct complex classifiers that combine relatively weak contributions of up to thousands of genes (attributes) to classify a disease. The complexity of such classifiers limits their transparency and consequently the biological insights they can provide. The goal of this study is to apply to this domain the methodology of constructing simple yet robust logic-based classifiers amenable to direct expert interpretation. On two well-known, publicly available gene expression classification problems, the paper shows the feasibility of this approach, employing a recently developed subgroup discovery methodology. Some of the discovered classifiers allow for novel biological interpretations.

journal_name

J Biomed Inform

journal_title

Journal of biomedical informatics

authors

Gamberger D,Lavrac N,Zelezný F,Tolar J

doi

10.1016/j.jbi.2004.07.007

keywords:

subject

Has Abstract

pub_date

2004-08-01 00:00:00

pages

269-84

issue

4

eissn

1532-0464

issn

1532-0480

pii

S1532-0464(04)00075-9

journal_volume

37

pub_type

杂志文章

相关文献

JOURNAL OF BIOMEDICAL INFORMATICS文献大全
  • Monitoring Obstructive Sleep Apnea by means of a real-time mobile system based on the automatic extraction of sets of rules through Differential Evolution.

    abstract：:Real-time Obstructive Sleep Apnea (OSA) episode detection and monitoring are important for society in terms of an improvement in the health of the general population and of a reduction in mortality and healthcare costs. Currently, to diagnose OSA patients undergo PolySomnoGraphy (PSG), a complicated and invasive test ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2014.02.015

    authors： Sannino G,De Falco I,De Pietro G

    更新日期：2014-06-01 00:00:00

  • Knowledge-based personalized search engine for the Web-based Human Musculoskeletal System Resources (HMSR) in biomechanics.

    abstract：:Human musculoskeletal system resources of the human body are valuable for the learning and medical purposes. Internet-based information from conventional search engines such as Google or Yahoo cannot response to the need of useful, accurate, reliable and good-quality human musculoskeletal resources related to medical ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2012.11.001

    authors： Dao TT,Hoang TN,Ta XH,Tho MC

    更新日期：2013-02-01 00:00:00

  • A kernel-based clustering method for gene selection with gene expression data.

    abstract：:Gene selection is important for cancer classification based on gene expression data, because of high dimensionality and small sample size. In this paper, we present a new gene selection method based on clustering, in which dissimilarity measures are obtained through kernel functions. It searches for best weights of ge...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2016.05.007

    authors： Chen H,Zhang Y,Gutman I

    更新日期：2016-08-01 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

  • Systematic comparison of the protein-protein interaction databases from a user's perspective.

    abstract：:In absence of periodic systematic comparisons, biologists/bioinformaticians may be forced to make a subjective selection among the many protein-protein interaction (PPI) databases and tools. We conducted a comprehensive compilation and comparison of such resources. We compiled 375 PPI resources, short-listed 125 impor...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2020.103380

    authors： Bajpai AK,Davuluri S,Tiwary K,Narayanan S,Oguru S,Basavaraju K,Dayalan D,Thirumurugan K,Acharya KK

    更新日期：2020-03-01 00:00:00

  • Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

    abstract：:Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2016.03.002

    authors： Kumar M,Rath NK,Rath SK

    更新日期：2016-04-01 00:00:00

  • Does the use of structured reporting improve usability? A comparative evaluation of the usability of two approaches for findings reporting in a large-scale telecardiology context.

    abstract：:One of the main reasons that leads to a low adoption rate of telemedicine systems is poor usability. An aspect that influences usability during the reporting of findings is the input mode, e.g., if a free-text (FT) or a structured report (SR) interface is employed. The objective of our study is to compare the usabilit...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2014.07.002

    authors： Lacerda TC,von Wangenheim CG,von Wangenheim A,Giuliano I

    更新日期：2014-12-01 00:00:00

  • Predicting the function of transplanted kidney in long-term care processes: Application of a hybrid model.

    abstract：BACKGROUND:A tool that can predict the estimated glomerular filtration rate (eGFR) in routine daily care can help clinicians to make better decisions for kidney transplant patients and to improve transplantation outcome. In this paper, we proposed a hybrid prediction model for predicting a future value for eGFR during ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2019.103116

    authors： Rashidi Khazaee P,Bagherzadeh M J,Niazkhani Z,Pirnejad H

    更新日期：2019-03-01 00:00:00

  • Neural network-based approaches for biomedical relation classification: A review.

    abstract：:The explosive growth of biomedical literature has created a rich source of knowledge, such as that on protein-protein interactions (PPIs) and drug-drug interactions (DDIs), locked in unstructured free text. Biomedical relation classification aims to automatically detect and classify biomedical relations, which has gre...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章,评审

    doi：10.1016/j.jbi.2019.103294

    authors： Zhang Y,Lin H,Yang Z,Wang J,Sun Y,Xu B,Zhao Z

    更新日期：2019-11-01 00:00:00

  • A comparison of machine learning methods for the diagnosis of pigmented skin lesions.

    abstract：:We analyze the discriminatory power of k-nearest neighbors, logistic regression, artificial neural networks (ANNs), decision tress, and support vector machines (SVMs) on the task of classifying pigmented skin lesions as common nevi, dysplastic nevi, or melanoma. Three different classification tasks were used as benchm...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1006/jbin.2001.1004

    authors： Dreiseitl S,Ohno-Machado L,Kittler H,Vinterbo S,Billhardt H,Binder M

    更新日期：2001-02-01 00:00:00

  • Understanding infusion administration in the ICU through Distributed Cognition.

    abstract：:To understand how healthcare technologies are used in practice and evaluate them, researchers have argued for adopting the theoretical framework of Distributed Cognition (DC). This paper describes the methods and results of a study in which a DC methodology, Distributed Cognition for Teamwork (DiCoT), was applied to s...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2012.02.003

    authors： Rajkomar A,Blandford A

    更新日期：2012-06-01 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 development and validation of a simulation tool for health policy decision making.

    abstract：:Computer simulations have been used to model infectious diseases to examine the outcomes of alternative strategies for managing their spread. Methicillin resistant Staphylococcus aureus (MRSA) skin and soft tissue infections have become prominent in many communities and efforts are underway to reduce the spread of thi...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2010.03.013

    authors： Panchanathan SS,Petitti DB,Fridsma DB

    更新日期：2010-08-01 00:00:00

  • Utilizing online stochastic optimization on scheduling of intensity-modulate radiotherapy therapy (IMRT).

    abstract：:According to Ministry of Health and Welfare of Taiwan, cancer has been one of the major causes of death in Taiwan since 1982. The Intensive-Modulated Radiation Therapy (IMRT) is one of the most important radiotherapies of cancers, especially for Nasopharyngeal cancers, Digestive system cancers and Cervical cancers. Fo...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2020.103499

    authors： Chang WH,Lo SM,Chen TL,Chen JC,Wu HN

    更新日期：2020-08-01 00:00:00

  • Exploiting the contextual cues for bio-entity name recognition in biomedical literature.

    abstract：:To extract biomedical information about bio-entities from the huge amount of biomedical literature, the first key step is recognizing their names in these literatures, which remains a challenging task due to the irregularities and ambiguities in bio-entities nomenclature. The recognition performances of the current po...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2008.01.002

    authors： Yang Z,Lin H,Li Y

    更新日期：2008-08-01 00:00:00

  • Enhancing phylogeography by improving geographical information from GenBank.

    abstract：:Phylogeography is a field that focuses on the geographical lineages of species such as vertebrates or viruses. Here, geographical data, such as location of a species or viral host is as important as the sequence information extracted from the species. Together, this information can help illustrate the migration of the...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2011.06.005

    authors： Scotch M,Sarkar IN,Mei C,Leaman R,Cheung KH,Ortiz P,Singraur A,Gonzalez G

    更新日期：2011-12-01 00:00:00

  • RedMed: Extending drug lexicons for social media applications.

    abstract：:Social media has been identified as a promising potential source of information for pharmacovigilance. The adoption of social media data has been hindered by the massive and noisy nature of the data. Initial attempts to use social media data have relied on exact text matches to drugs of interest, and therefore suffer ...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2019.103307

    authors： Lavertu A,Altman RB

    更新日期：2019-11-01 00:00:00

  • Temporal phenotyping of medically complex children via PARAFAC2 tensor factorization.

    abstract：OBJECTIVE:Our aim is to extract clinically-meaningful phenotypes from longitudinal electronic health records (EHRs) of medically-complex children. This is a fragile set of patients consuming a disproportionate amount of pediatric care resources but who often end up with sub-optimal clinical outcome. The rise in availab...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2019.103125

    authors： Perros I,Papalexakis EE,Vuduc R,Searles E,Sun J

    更新日期：2019-05-01 00:00:00

  • A new framework for the selection of tag SNPs by multimarker haplotypes.

    abstract：:This paper proposes a new framework for the selection of tag SNPs based on haplotypes instead of on a single SNP. The tag SNPs found by this framework form a set of haplotypes completely predictive of the alleles of all untyped SNPs. We refer to this problem as MTMH, which is defined as follows: given a set of SNPs, f...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2008.04.003

    authors： Huang YT,Chao KM

    更新日期：2008-12-01 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

  • Visual aggregate analysis of eligibility features of clinical trials.

    abstract：OBJECTIVE:To develop a method for profiling the collective populations targeted for recruitment by multiple clinical studies addressing the same medical condition using one eligibility feature each time. METHODS:Using a previously published database COMPACT as the backend, we designed a scalable method for visual aggr...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2015.01.005

    authors： He Z,Carini S,Sim I,Weng C

    更新日期：2015-04-01 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

  • Inductive creation of an annotation schema for manually indexing clinical conditions from emergency department reports.

    abstract：:Evaluating automated indexing applications requires comparing automatically indexed terms against manual reference standard annotations. However, there are no standard guidelines for determining which words from a textual document to include in manual annotations, and the vague task can result in substantial variation...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2005.06.004

    authors： Chapman WW,Dowling JN

    更新日期：2006-04-01 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

  • Serum cancer biomarker discovery through analysis of gene expression data sets across multiple tumor and normal tissues.

    abstract：:The development of convenient serum bioassays for cancer screening, diagnosis, prognosis, and monitoring of treatment is one of top priorities in cancer research community. Although numerous biomarker candidates have been generated by applying high-throughput technologies such as transcriptomics, proteomics, and metab...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2011.08.010

    authors： Jin H,Lee HC,Park SS,Jeong YS,Kim SY

    更新日期：2011-12-01 00:00:00

  • Patient similarity for precision medicine: A systematic review.

    abstract：:Evidence-based medicine is the most prevalent paradigm adopted by physicians. Clinical practice guidelines typically define a set of recommendations together with eligibility criteria that restrict their applicability to a specific group of patients. The ever-growing size and availability of health-related data is cur...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2018.06.001

    authors： Parimbelli E,Marini S,Sacchi L,Bellazzi R

    更新日期：2018-07-01 00:00:00

  • Collaborative text-annotation resource for disease-centered relation extraction from biomedical text.

    abstract：:Agglomerating results from studies of individual biological components has shown the potential to produce biomedical discovery and the promise of therapeutic development. Such knowledge integration could be tremendously facilitated by automated text mining for relation extraction in the biomedical literature. Relation...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2009.02.001

    authors： Cano C,Monaghan T,Blanco A,Wall DP,Peshkin L

    更新日期：2009-10-01 00:00:00

  • Prediction of clinical risks by analysis of preclinical and clinical adverse events.

    abstract：:This study examines the ability of nonclinical adverse event observations to predict human clinical adverse events observed in drug development programs. In addition it examines the relationship between nonclinical and clinical adverse event observations to drug withdrawal and proposes a model to predict drug withdraw...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2015.02.008

    authors： Clark M

    更新日期：2015-04-01 00:00:00

  • Unsupervised low-dimensional vector representations for words, phrases and text that are transparent, scalable, and produce similarity metrics that are not redundant with neural embeddings.

    abstract：:Neural embeddings are a popular set of methods for representing words, phrases or text as a low dimensional vector (typically 50-500 dimensions). However, it is difficult to interpret these dimensions in a meaningful manner, and creating neural embeddings requires extensive training and tuning of multiple parameters a...

    journal_title：Journal of biomedical informatics

    pub_type： 杂志文章

    doi：10.1016/j.jbi.2019.103096

    authors： Smalheiser NR,Cohen AM,Bonifield G

    更新日期：2019-02-01 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