An optimization based on simulation approach to the patient admission scheduling problem using a linear programing algorithm.

Abstract:

BACKGROUND:As patient's length of stay in waiting lists increases, governments are looking for strategies to control the problem. Agreements were created with private providers to diminish the workload in the public sector. However, the growth of the private sector is not following the demand for care. Given this context, new management strategies have to be considered in order to minimize patient length of stay in waiting lists while reducing the costs and increasing (or at least maintaining) the quality of care. METHOD:Appointment scheduling systems are today known to be proficient in the optimization of health care services. Their utilization is focused on increasing the usage of human resources, medical equipment and reducing the patient waiting times. In this paper, a simulation-based optimization approach to the Patient Admission Scheduling Problem is presented. Modeling tools and simulation techniques are used in the optimization of a diagnostic imaging department. RESULTS:The proposed techniques have demonstrated to be effective in the evaluation of diagnostic imaging workflows. A simulated annealing algorithm was used to optimize the patient admission sequence towards minimizing the total completion and total waiting of patients. The obtained results showed average reductions of 5% on the total completion and 38% on the patients' total waiting time.

journal_name

J Biomed Inform

authors

Granja C,Almada-Lobo B,Janela F,Seabra J,Mendes A

doi

10.1016/j.jbi.2014.08.007

subject

Has Abstract

pub_date

2014-12-01 00:00:00

pages

427-37

eissn

1532-0464

issn

1532-0480

pii

S1532-0464(14)00188-9

journal_volume

52

pub_type

杂志文章
  • Developing EHR-driven heart failure risk prediction models using CPXR(Log) with the probabilistic loss function.

    abstract::Computerized survival prediction in healthcare identifying the risk of disease mortality, helps healthcare providers to effectively manage their patients by providing appropriate treatment options. In this study, we propose to apply a classification algorithm, Contrast Pattern Aided Logistic Regression (CPXR(Log)) wit...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2016.01.009

    authors: Taslimitehrani V,Dong G,Pereira NL,Panahiazar M,Pathak J

    更新日期:2016-04-01 00:00:00

  • A comparison of word embeddings for the biomedical natural language processing.

    abstract:BACKGROUND:Word embeddings have been prevalently used in biomedical Natural Language Processing (NLP) applications due to the ability of the vector representations being able to capture useful semantic properties and linguistic relationships between words. Different textual resources (e.g., Wikipedia and biomedical lit...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2018.09.008

    authors: Wang Y,Liu S,Afzal N,Rastegar-Mojarad M,Wang L,Shen F,Kingsbury P,Liu H

    更新日期:2018-11-01 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

  • Deep learning with wearable based heart rate variability for prediction of mental and general health.

    abstract::The ubiquity and commoditisation of wearable biosensors (fitness bands) has led to a deluge of personal healthcare data, but with limited analytics typically fed back to the user. The feasibility of feeding back more complex, seemingly unrelated measures to users was investigated, by assessing whether increased levels...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2020.103610

    authors: Coutts LV,Plans D,Brown AW,Collomosse J

    更新日期:2020-12-01 00:00:00

  • Wisdom of artificial crowds feature selection in untargeted metabolomics: An application to the development of a blood-based diagnostic test for thrombotic myocardial infarction.

    abstract:INTRODUCTION:Heart disease remains a leading cause of global mortality. While acute myocardial infarction (colloquially: heart attack), has multiple proximate causes, proximate etiology cannot be determined by a blood-based diagnostic test. We enrolled a suitable patient cohort and conducted a non-targeted quantificati...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章,多中心研究

    doi:10.1016/j.jbi.2018.03.007

    authors: Trainor PJ,Yampolskiy RV,DeFilippis AP

    更新日期:2018-05-01 00:00:00

  • Decision-making model for early diagnosis of congestive heart failure using rough set and decision tree approaches.

    abstract::The accurate diagnosis of heart failure in emergency room patients is quite important, but can also be quite difficult due to our insufficient understanding of the characteristics of heart failure. The purpose of this study is to design a decision-making model that provides critical factors and knowledge associated wi...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2012.04.013

    authors: Son CS,Kim YN,Kim HS,Park HS,Kim MS

    更新日期:2012-10-01 00:00:00

  • Transitive closure of subsumption and causal relations in a large ontology of radiological diagnosis.

    abstract::The Radiology Gamuts Ontology (RGO)-an ontology of diseases, interventions, and imaging findings-was developed to aid in decision support, education, and translational research in diagnostic radiology. The ontology defines a subsumption (is_a) relation between more general and more specific terms, and a causal relatio...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2016.03.015

    authors: Kahn CE Jr

    更新日期:2016-06-01 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

  • A cascaded approach for Chinese clinical text de-identification with less annotation effort.

    abstract::With rapid adoption of Electronic Health Records (EHR) in China, an increasing amount of clinical data has been available to support clinical research. Clinical data secondary use usually requires de-identification of personal information to protect patient privacy. Since manually de-identification of free clinical te...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2017.07.017

    authors: Jian Z,Guo X,Liu S,Ma H,Zhang S,Zhang R,Lei J

    更新日期:2017-09-01 00:00:00

  • An automated reasoning framework for translational research.

    abstract::In this paper we propose a novel approach to the design and implementation of knowledge-based decision support systems for translational research, specifically tailored to the analysis and interpretation of data from high-throughput experiments. Our approach is based on a general epistemological model of the scientifi...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2009.11.005

    authors: Riva A,Nuzzo A,Stefanelli M,Bellazzi R

    更新日期:2010-06-01 00:00:00

  • A private DNA motif finding algorithm.

    abstract::With the increasing availability of genomic sequence data, numerous methods have been proposed for finding DNA motifs. The discovery of DNA motifs serves a critical step in many biological applications. However, the privacy implication of DNA analysis is normally neglected in the existing methods. In this work, we pro...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2013.12.016

    authors: Chen R,Peng Y,Choi B,Xu J,Hu H

    更新日期:2014-08-01 00:00:00

  • Cadec: A corpus of adverse drug event annotations.

    abstract::CSIRO Adverse Drug Event Corpus (Cadec) is a new rich annotated corpus of medical forum posts on patient-reported Adverse Drug Events (ADEs). The corpus is sourced from posts on social media, and contains text that is largely written in colloquial language and often deviates from formal English grammar and punctuation...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2015.03.010

    authors: Karimi S,Metke-Jimenez A,Kemp M,Wang C

    更新日期:2015-06-01 00:00:00

  • Unleashing genotypes in epidemiology - A novel method for managing high throughput information.

    abstract::The large amounts of data generated when high-throughput genotyping methods are used in large-scale epidemiological studies (>10,000 participants) present an enormous challenge to researchers in terms of structured data management. In order to face these challenges, a system has been designed and implemented where gen...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2009.07.005

    authors: Olund G,Brinne A,Lindqvist P,Litton JE

    更新日期:2009-12-01 00:00:00

  • DiseaSE: A biomedical text analytics system for disease symptom extraction and characterization.

    abstract::Due to increasing volume and unstructured nature of the scientific literatures in biomedical domain, most of the information embedded within them remain untapped. This paper presents a biomedical text analytics system, DiseaSE (Disease Symptom Extraction), to identify and extract disease symptoms and their association...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2019.103324

    authors: Abulaish M,Parwez MA,Jahiruddin

    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

  • Comparison of reversible-jump Markov-chain-Monte-Carlo learning approach with other methods for missing enzyme identification.

    abstract::Computational identification of missing enzymes plays a significant role in accurate and complete reconstruction of metabolic network for both newly sequenced and well-studied organisms. For a metabolic reaction, given a set of candidate enzymes identified according to certain biological evidences, a powerful mathemat...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2007.09.002

    authors: Geng B,Zhou X,Zhu J,Hung YS,Wong ST

    更新日期:2008-04-01 00:00:00

  • HBLAST: Parallelised sequence similarity--A Hadoop MapReducable basic local alignment search tool.

    abstract::The recent exponential growth of genomic databases has resulted in the common task of sequence alignment becoming one of the major bottlenecks in the field of computational biology. It is typical for these large datasets and complex computations to require cost prohibitive High Performance Computing (HPC) to function....

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2015.01.008

    authors: O'Driscoll A,Belogrudov V,Carroll J,Kropp K,Walsh P,Ghazal P,Sleator RD

    更新日期:2015-04-01 00:00:00

  • Classification of ADHD with bi-objective optimization.

    abstract::Attention Deficit Hyperactive Disorder (ADHD) is one of the most common diseases in school aged children. In this paper, we consider using fMRI data with classification techniques to aid the diagnosis of ADHD and propose a bi-objective ADHD classification scheme based on L1-norm support vector machine (SVM). In our cl...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2018.07.011

    authors: Shao L,Xu Y,Fu D

    更新日期:2018-08-01 00:00:00

  • Vaidurya: a multiple-ontology, concept-based, context-sensitive clinical-guideline search engine.

    abstract::We designed and implemented a generic search engine (Vaidurya), as part of our Digital clinical-Guideline Library (DeGeL) framework. Two search methods were implemented in addition to full-text search: (1) concept-based search, which relies on pre-indexing the guidelines in a clinically meaningful fashion, and (2) con...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2008.07.003

    authors: Moskovitch R,Shahar Y

    更新日期:2009-02-01 00:00:00

  • Evaluating warfarin dosing models on multiple datasets with a novel software framework and evolutionary optimisation.

    abstract::Warfarin is an effective preventative treatment for arterial and venous thromboembolism, but requires individualised dosing due to its narrow therapeutic range and high individual variation. Many machine learning techniques have been demonstrated in this domain. This study evaluated the accuracy of the most promising ...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2020.103634

    authors: Truda G,Marais P

    更新日期:2021-01-01 00:00:00

  • Personal health information in research: Perceived risk, trustworthiness and opinions from patients attending a tertiary healthcare facility.

    abstract:BACKGROUND:Personal health information is a valuable resource to the advancement of research. In order to achieve a comprehensive reform of data infrastructure in Australia, both public engagement and building social trust is vital. In light of this, we conducted a study to explore the opinions, perceived risks and tru...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2019.103222

    authors: Krahe M,Milligan E,Reilly S

    更新日期:2019-07-01 00:00:00

  • Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: an application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39).

    abstract::Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learni...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2012.07.010

    authors: Borchani H,Bielza C,Martı Nez-Martı N P,Larrañaga P

    更新日期:2012-12-01 00:00:00

  • Comparing image search behaviour in the ARRS GoldMiner search engine and a clinical PACS/RIS.

    abstract::Information search has changed the way we manage knowledge and the ubiquity of information access has made search a frequent activity, whether via Internet search engines or increasingly via mobile devices. Medical information search is in this respect no different and much research has been devoted to analyzing the w...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2015.04.013

    authors: De-Arteaga M,Eggel I,Do B,Rubin D,Kahn CE Jr,Müller H

    更新日期:2015-08-01 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

  • 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

  • Integrating cancer diagnosis terminologies based on logical definitions of SNOMED CT concepts.

    abstract::In oncology, the reuse of data is confronted with the heterogeneity of terminologies. It is necessary to semantically integrate these distinct terminologies. The semantic integration by using a third terminology as a support is a conventional approach for the integration of two terminologies that are not very structur...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2017.08.013

    authors: Nikiema JN,Jouhet V,Mougin F

    更新日期:2017-10-01 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

  • 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

  • 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

  • Computing with evidence Part II: An evidential approach to predicting metabolic drug-drug interactions.

    abstract::We describe a novel experiment that we conducted with the Drug Interaction Knowledge-base (DIKB) to determine which combinations of evidence enable a rule-based theory of metabolic drug-drug interactions to make the most optimal set of predictions. The focus of the experiment was a group of 16 drugs including six memb...

    journal_title:Journal of biomedical informatics

    pub_type: 杂志文章

    doi:10.1016/j.jbi.2009.05.010

    authors: Boyce R,Collins C,Horn J,Kalet I

    更新日期:2009-12-01 00:00:00