Computer methods and programs in biomedicine

Publications in this journal

• Article: Computer assessment of indirect insight during an airflow interrupter maneuver of breathing.

  Ireneusz Jabłoński
  [show abstract] [hide abstract]
  ABSTRACT: The paper answers the questions if it is possible to conclude in objective way on more (than one -Rint - in a classical IT) number of parameters from the time domain post-interrupter signals during the occlusional measurement of respiratory mechanics and also verifies what accuracy can be achieved in such attempt. To obtain reported results, the time-domain enhanced interrupter technique (TD-EIT) was developed in this paper using computer simulations. Three-stage scheme of work was assumed in the project. First, the quality of the model identification was assessed for various combinations of pressure and flow signals recorded during the interruption. Then, the correlation between the working characteristics of the interrupter valve and the precision of the parameter estimation were assessed for the TD-EIT algorithm. Finally, a verification experiment by forward-inverse modeling was organized, in which the mechanical characteristics of a complex model were mapped with reduced analogs and with the use of neural networks for three typical modes: 'Normal state', 'Airway constriction' and 'Cheeks supported'. Obtained results show that to became effective in time-domain post-interrupter data exploration, both pressure and flow signals should be used in assessment of respiratory mechanics, taken in a range of at least 100ms and when both slopes (valve closing and opening) of quasi-step excitation are included. What is more, the faster the valve the smaller error of parameter estimation in proposed TD-EIT was observed, and this uncertainty importantly falls down for the length of time window exceeding the limit of 100ms. The pioneering use of neural network for mapping the mechanical properties of lungs with the use of interrupter experiment methodology proves that it is possible to conclude about more (than one) number of parameters characterizing the complex system and that this insight is biased with the error not exceeding of 10%; only peripheral properties are estimated worse. Such observation has a potential to change the experimental protocol, which was used in interrupter measurements up to date and to make this technique more attractive in comparison to other method, i.e. forced oscillation technique or impulse oscillometry. As regards the practical meaning of reported results for engineers and end-users (physicians and patients), proposed solution can be applied in simple portable devices with a feature of easy operation (important for e-monitoring).
  Computer methods and programs in biomedicine 06/2013; 110(3):320-32.
• Article: A novel neural network approach to cDNA microarray image segmentation.

  Zidong Wang, Bachar Zineddin, Jinling Liang, Nianyin Zeng, Yurong Li, Min Du, Jie Cao, Xiaohui Liu
  [show abstract] [hide abstract]
  ABSTRACT: Microarray technology has become a great source of information for biologists to understand the workings of DNA which is one of the most complex codes in nature. Microarray images typically contain several thousands of small spots, each of which represents a different gene in the experiment. One of the key steps in extracting information from a microarray image is the segmentation whose aim is to identify which pixels within an image represent which gene. This task is greatly complicated by noise within the image and a wide degree of variation in the values of the pixels belonging to a typical spot. In the past there have been many methods proposed for the segmentation of microarray image. In this paper, a new method utilizing a series of artificial neural networks, which are based on multi-layer perceptron (MLP) and Kohonen networks, is proposed. The proposed method is applied to a set of real-world cDNA images. Quantitative comparisons between the proposed method and commercial software GenePix(®) are carried out in terms of the peak signal-to-noise ratio (PSNR). This method is shown to not only deliver results comparable and even superior to existing techniques but also have a faster run time.
  Computer methods and programs in biomedicine 05/2013;
• Article: RDFBuilder: A tool to automatically build RDF-based interfaces for MAGE-OM microarray data sources.

  Alberto Anguita, Luis Martin, Miguel Garcia-Remesal, Victor Maojo
  [show abstract] [hide abstract]
  ABSTRACT: This paper presents RDFBuilder, a tool that enables RDF-based access to MAGE-ML-compliant microarray databases. We have developed a system that automatically transforms the MAGE-OM model and microarray data stored in the ArrayExpress database into RDF format. Additionally, the system automatically enables a SPARQL endpoint. This allows users to execute SPARQL queries for retrieving microarray data, either from specific experiments or from more than one experiment at a time. Our system optimizes response times by caching and reusing information from previous queries. In this paper, we describe our methods for achieving this transformation. We show that our approach is complementary to other existing initiatives, such as Bio2RDF, for accessing and retrieving data from the ArrayExpress database.
  Computer methods and programs in biomedicine 05/2013;
• Article: Automatic classification of the interferential tear film lipid layer using colour texture analysis.

  B Remeseiro, M Penas, N Barreira, A Mosquera, J Novo, C García-Resúa
  [show abstract] [hide abstract]
  ABSTRACT: The tear film lipid layer is heterogeneous among the population. Its classification depends on its thickness and can be done using the interference pattern categories proposed by Guillon. This papers presents an exhaustive study about the characterisation of the interference phenomena as a texture pattern, using different feature extraction methods in different colour spaces. These methods are first analysed individually and then combined to achieve the best results possible. The principal component analysis (PCA) technique has also been tested to reduce the dimensionality of the feature vectors. The proposed methodologies have been tested on a dataset composed of 105 images from healthy subjects, with a classification rate of over 95% in some cases.
  Computer methods and programs in biomedicine 05/2013;
• Article: GREMET: An integrative tool for the prediction of mutation effects on gene regulation.

  Polykarpos Athanasiadis, Andigoni Malousi, Sofia Kouidou, Nicos Maglaveras
  [show abstract] [hide abstract]
  ABSTRACT: The identification of thousands of mutations yearly has put new challenges to researchers who are interested in fast and effective annotation as well as the prediction of potential implications to the gene regulation mechanisms. This work presents an integrative tool, called GREMET, for the prediction of alterations in gene splicing regulation inferred by mutations of the human genome. GREMET supports the characterization of mutations either single-point or indels with respect to their effect on the splicing potential of the neighboring sequences and the binding strength of auxiliary cis-acting splicing enhancers. In addition, GREMET identifies possible consequences of mutations on the DNA methylation through the disruption or creation of CpG sequences. Besides locus-specific mutations, GREMET performs the analyses on newly identified mutations and provides an easy-to-use Web interface helping researchers to save time in routine mutation analyses. GREMET is freely accessible at: http://kedip.med.auth.gr/biotools/gremet/.
  Computer methods and programs in biomedicine 05/2013;
• Article: Computer-aided diagnosis of breast masses using quantified BI-RADS findings.

  Woo Kyung Moon, Chung-Ming Lo, Nariya Cho, Jung Min Chang, Chiun-Sheng Huang, Jeon-Hor Chen, Ruey-Feng Chang
  [show abstract] [hide abstract]
  ABSTRACT: The information from radiologists was utilized in the proposed computer-aided diagnosis (CAD) for breast tumor classification. The ultrasound (US) database used in this study contained 166 benign and 78 malignant masses. For each mass, six quantitative feature sets were used to describe the radiologists' grading of six Breast Imaging Reporting and Data System (BI-RADS) categories including shape, orientation, margins, lesion boundary, echo pattern, and posterior acoustic features on breast US. The descriptive abilities were between 76% and 82% and the predicted descriptors were then used for tumor classification. Using receiver operating characteristic curve for evaluation, the area under curve (AUC) of the proposed CAD was slightly better than that of a conventional CAD based on the combination of all quantitative features (0.96 vs. 0.93, p=0.18). The partial AUC over 90% sensitivity of the proposed CAD was significantly better than that of the conventional CAD (0.90 vs. 0.76, p<0.05). In conclusion, the computer-aided analysis with qualitative information from radiologists showed a promising result for breast tumor classification.
  Computer methods and programs in biomedicine 04/2013;
• Article: Necessity of noise in physiology and medicine.

  Ervin Sejdić, Lewis A Lipsitz
  [show abstract] [hide abstract]
  ABSTRACT: Noise is omnipresent in biomedical systems and signals. Conventional views assume that its presence is detrimental to systems' performance and accuracy. Hence, various analytic approaches and instrumentation have been designed to remove noise. On the contrary, recent contributions have shown that noise can play a beneficial role in biomedical systems. The results of this literature review indicate that noise is an essential part of biomedical systems and often plays a fundamental role in the performance of these systems. Furthermore, in preliminary work, noise has demonstrated therapeutic potential to alleviate the effects of various diseases. Further research into the role of noise and its applications in medicine is likely to lead to novel approaches to the treatment of diseases and prevention of disability.
  Computer methods and programs in biomedicine 04/2013;
• Article: Warehousing re-annotated cancer genes for biomarker meta-analysis.

  M Orsini, A Travaglione, E Capobianco
  [show abstract] [hide abstract]
  ABSTRACT: Translational research in cancer genomics assigns a fundamental role to bioinformatics in support of candidate gene prioritization with regard to both biomarker discovery and target identification for drug development. Efforts in both such directions rely on the existence and constant update of large repositories of gene expression data and omics records obtained from a variety of experiments. Users who interactively interrogate such repositories may have problems in retrieving sample fields that present limited associated information, due for instance to incomplete entries or sometimes unusable files. Cancer-specific data sources present similar problems. Given that source integration usually improves data quality, one of the objectives is keeping the computational complexity sufficiently low to allow an optimal assimilation and mining of all the information. In particular, the scope of integrating intraomics data can be to improve the exploration of gene co-expression landscapes, while the scope of integrating interomics sources can be that of establishing genotype-phenotype associations. Both integrations are relevant to cancer biomarker meta-analysis, as the proposed study demonstrates. Our approach is based on re-annotating cancer-specific data available at the EBI's ArrayExpress repository and building a data warehouse aimed to biomarker discovery and validation studies. Cancer genes are organized by tissue with biomedical and clinical evidences combined to increase reproducibility and consistency of results. For better comparative evaluation, multiple queries have been designed to efficiently address all types of experiments and platforms, and allow for retrieval of sample-related information, such as cell line, disease state and clinical aspects.
  Computer methods and programs in biomedicine 04/2013;
• Article: Software for symptom association analysis in pediatric gastroesophageal reflux disease.

  Alejandro Barriga-Rivera, Mar Elena, Maria Jose Moya, Manuel Lopez-Alonso
  [show abstract] [hide abstract]
  ABSTRACT: Gastroesophageal reflux (GER) disease is a serious complication of the upper gastrointestinal tract. Cardiorespiratory symptoms such as apnea, oxygen desaturation and bradycardia may be related to GER. Thus, the recommended diagnostic methodology in pediatric patients requires 24-h synchronized esophageal and cardiorespiratory monitoring. However, there is no computer tool available for this purpose and therefore, researchers and physicians are forced to seek for customized solutions. This paper presents an open source computer program for the analysis of symptom association. It allows a convenient visualization of the biological signals and implements the three main metrics for symptom association, that is, the symptom index, the symptom sensitivity index and the symptom association probability. This software represents a flexible solution and will facilitate caregivers an easy assessment of the existence of temporal association between GER and cardiorespiratory episodes. This would ideally reduce inappropriate medical and surgical treatments and would provide an early diagnosis of the medical condition.
  Computer methods and programs in biomedicine 04/2013;
• Article: SAKE: A new quantification tool for positron emission tomography studies.

  Mattia Veronese, Gaia Rizzo, Federico E Turkheimer, Alessandra Bertoldo
  [show abstract] [hide abstract]
  ABSTRACT: In dynamic positron emission tomography (PET) studies, spectral analysis (SA) refers to a data-driven quantification method, based on a single-input single-output model for which the transfer function is described by a sum of exponential terms. SA allows to quantify numerosities, amplitudes and eigenvalues of the transfer function allowing, in this way, to separate kinetic components of the tissue tracer activity with minimal model assumptions. The SA model can be solved with a linear estimator alone or with numerical filters, resulting in different types of SA approaches. Once estimated the number, amplitudes and eigenvalues of the transfer function, one can distinguish the presence in the system of irreversible and/or reversible components as well as derive parameters of physiological significance. These characteristics make it an appealing alternative method to compartmental models which are widely used for the quantitative analysis of dynamic studies acquired with PET. However, despite its applicability to a large number of PET tracers, its implementation is not straightforward and its utilization in the nuclear medicine community has been limited especially by the lack of an user-friendly software application. In this paper we proposed SAKE, a computer program for the quantitative analysis of PET data through the main SA methods. SAKE offers a unified pipeline of analysis usable also by people with limited computer knowledge but with high interest in SA.
  Computer methods and programs in biomedicine 04/2013;
• Article: Physicians' responses to computerized drug-drug interaction alerts for outpatients.

  Min-Li Yeh, Ying-Jui Chang, Po-Yen Wang, Yu-Chuan Jack Li, Chien-Yeh Hsu
  [show abstract] [hide abstract]
  ABSTRACT: INTRODUCTION: Adverse drug reactions (ADR) increase morbidity and mortality; potential drug-drug interactions (DDI) increase the probability of ADR. Studies have proven that computerized drug-interaction alert systems (DIAS) might reduce medication errors and potential adverse events. However, the relatively high override rates obscure the benefits of alert systems, which result in barriers for availability. It is important to understand the frequency at which physicians override DIAS and the reasons for overriding reminders. METHOD: All the DDI records of outpatient prescriptions from a tertiary university hospital from 2005 and 2006 detections by the DIAS are included in the study. The DIAS is a JAVA language software that was integrated into the computerized physician order entry system. The alert window is displayed when DDIs occur during order entries, and physicians choose the appropriate action according to the DDI alerts. There are seven response choices are obligated in representing overriding and acceptance: (1) necessary order and override; (2) expected DDI and override; (3) expected DDI with modified dosage and override; (4) no DDI and override; (5) too busy to respond and override; (6) unaware of the DDI and accept; and (7) unexpected DDI and accept. The responses were collected for analysis. RESULTS: A total of 11,084 DDI alerts of 1,243,464 outpatient prescriptions were present, 0.89% of all computerized prescriptions. The overall rate for accepting was 8.5%, but most of the alerts were overridden (91.5%). Physicians of family medicine and gynecology-obstetrics were more willing to accept the alerts with acceptance rates of 20.8% and 20.0% respectively (p<0.001). Information regarding the recognition of DDIs indicated that 82.0% of the DDIs were aware by physicians, 15.9% of DDIs were unaware by physicians, and 2.1% of alerts were ignored. The percentage of total alerts declined from 1.12% to 0.79% during 24 months' study period, and total overridden alerts also declined (from 1.04% to 0.73%). CONCLUSION: We explored the physicians' behavior by analyzing responses to the DDI alerts. Although the override rate is still high, the reasons why physicians may override DDI alerts were well analyzed and most DDI were recognized by physicians. Nonetheless, the trend of total overrides is in decline, which indicates a learning curve effect from exposure to DIAS. By analyzing the computerized responses provided by physicians, efforts should be made to improve the efficiency of the DIAS, and pharmacists, as well as patient safety staffs, can catch physicians' appropriate reasons for overriding DDI alerts, improving patient safety.
  Computer methods and programs in biomedicine 04/2013;
• Article: A novel tool for segmenting 3D medical images based on generalized cylinders and active surfaces.

  Konstantinos K Delibasis, Aristides Kechriniotis, I Maglogiannis
  [show abstract] [hide abstract]
  ABSTRACT: Three-dimensional (3D) medical imaging has been incorporated in routine clinical practice, since the required infrastructure has become increasingly affordable. New algorithms and applications are needed to serve the additional image processing and analysis functions in 3D space. In this work we propose a system for semi-automatic modeling and segmentation of elongated salient and anatomical objects in 3D medical images. The proposed methodology is based on a novel mathematical formalization of a well-known class of geometric primitives, namely generalized cylinders (GCs), which exhibits advantages over the existing parametric definition. Since the anatomical objects have to be modeled by their intersection with the transverse image planes, the proposed methodology includes also a new seeded region growing (SRG) segmentation algorithm for ellipse detection in 2D images, based on a priori shape knowledge. Finally, the resulting GC model is used to initialize an active surface (AS) segmentation method, in order to accurately delineate the required object. In this work we present the proposed algorithms in detail, along with the evaluation of the accuracy of the model-based segmentation by experts. Results show that elongated objects like the aorta and the trachea may be segmented with sensitivity between 90% and 95%. The proposed SRG-ellipse detector requires minimal user-initialization and its executions requires only few seconds for each image slice on an average laptop. The evolution of the AS requires less than one second per iteration for a typical CT image. Comparisons are provided with state of the art semi-automatic medical image processing software, which validate the merit of the proposed work.
  Computer methods and programs in biomedicine 04/2013;
• Article: Genetic algorithms as a useful tool for trabecular and cortical bone segmentation.

  K Janc, J Tarasiuk, A S Bonnet, P Lipinski
  [show abstract] [hide abstract]
  ABSTRACT: The aim of this study was to find a semi-automatic method of bone segmentation on the basis of computed tomography (CT) scan series in order to recreate corresponding 3D objects. So, it was crucial for the segmentation to be smooth between adjacent scans. The concept of graphics pipeline computing was used, i.e. simple graphics filters such as threshold or gradient were processed in a manner that the output of one filter became the input of the second one resulting in so called pipeline. The input of the entire stream was the CT scan and the output corresponded to the binary mask showing where a given tissue is located in the input image. In this approach the main task consists in finding the suitable sequence, types and parameters of graphics filters building the pipeline. Because of the high number of desired parameters (in our case 96), it was decided to use a slightly modified genetic algorithm. To determine fitness value, the mask obtained from the parameters found through genetic algorithms (GA) was compared with those manually prepared. The numerical value corresponding to such a comparison has been defined by Dice's coefficient. Preparation of reference masks for a few scans among the several hundreds of them was the only action done manually by a human expert. Using this method, very good results both for trabecular and cortical bones were obtained. It has to be emphasized that as no real border exists between these two bone types, the manually prepared reference masks were quite conventional and therefore charged with errors. As GA is a non-deterministic method, the present work also contains a statistical analysis of the relations existing between various GA parameters and fitness function. Finally the best sets of the GA parameters are proposed.
  Computer methods and programs in biomedicine 04/2013;
• Article: Debris removal in Pap-smear images.

  Patrik Malm, Byju N Balakrishnan, Vilayil K Sujathan, Rajesh Kumar, Ewert Bengtsson
  [show abstract] [hide abstract]
  ABSTRACT: Since its introduction in the 1940s the Pap-smear test has helped reduce the incidence of cervical cancer dramatically in countries where regular screening is standard. The automation of this procedure is an open problem that has been ongoing for over fifty years without reaching satisfactory results. Existing systems are discouragingly expensive and yet they are only able to make a correct distinction between normal and abnormal samples in a fraction of cases. Therefore, they are limited to acting as support for the cytotechnicians as they perform their manual screening. The main reason for the current limitations is that the automated systems struggle to overcome the complexity of the cell structures. Samples are covered in artefacts such as blood cells, overlapping and folded cells, and bacteria, that hamper the segmentation processes and generate large number of suspicious objects. The classifiers designed to differentiate between normal cells and pre-cancerous cells produce unpredictable results when classifying artefacts. In this paper, we propose a sequential classification scheme focused on removing unwanted objects, debris, from an initial segmentation result, intended to be run before the actual normal/abnormal classifier. The method has been evaluated using three separate datasets obtained from cervical samples prepared using both the standard Pap-smear approach as well as the more recent liquid based cytology sample preparation technique. We show success in removing more than 99% of the debris without loosing more than around one percent of the epithelial cells detected by the segmentation process.
  Computer methods and programs in biomedicine 04/2013;
• Article: PODSE: A computer program for optimal design of trials with discrete-time survival endpoints.

  Katarzyna Jóźwiak, Mirjam Moerbeek
  [show abstract] [hide abstract]
  ABSTRACT: In experimental settings, one or more groups of subjects receive a treatment and they are compared to a group of subjects that receives a standard treatment or no treatment at all. These compared groups might have an equal number of subjects or some of the groups might have more participants relative to the other groups. Moreover, subjects in these groups can be followed over a short or a long period. To conduct experiments in a sufficient way, researchers should find a good design in the planning phase of the trial. The optimal design for experimental studies on event occurrence with discrete-time survival endpoints where two treatment groups are followed over time, is an optimal combination of the number of time periods, the total number of participants in the trial and the proportion of subjects in the experimental group. It is easy to find the best design for such studies using the PODSE program.
  Computer methods and programs in biomedicine 04/2013;
• Article: Critical laboratory result reporting system in cancer patients.

  Chang-I Chen, James Miser, Ching-Feng Kuan, Yu-Ann Fang, Carlos Lam, Yu-Chuan Li
  [show abstract] [hide abstract]
  ABSTRACT: HYPOTHESIS: Automatic transmission of computer-generated Critical Laboratory Result Reports (CLRRs) to physicians can improve the care of advanced cancer patients by improving the communication efficacy of important medical information. METHOD: We followed a cohort of 2012 cancer patients from diagnosis to five years or to death if it occurred before five years from diagnosis. The incidence and number of CLRRs and their association with diagnosis, age, gender, tumor size, and clinical staging were evaluated. The CLRRs that were reported included for example: glucose<40 or>500, hemoglobin<6.0. (Appendix 1) RESULTS: Two thousand, twelve patients with cancer were included in the study; 45.6 percent had one or more critical laboratory results that required a CLRR. Older patients greater than or equal to 75 years of age had more CLRRs than younger patients. Patients with colorectal, liver, and lung cancer had a significantly higher number of CLRRs. More CLRRs were also seen in late-staged cancers. These conditions also have higher mortality rates. CONCLUSION: Critical values are common in patients with cancer, especially older patients with advanced disease. They occur more commonly with some cancers of liver and lung cancers. Our data demonstrate that critical laboratory values can be transmitted successfully to physicians. The impact of this system promises to improve the care of these individuals' serious illnesses. A prospective study to demonstrate the benefit of this system is being planned.
  Computer methods and programs in biomedicine 04/2013;
• Article: A minimally invasive surgery robotic assistant for HALS-SILS techniques.

  E Bauzano, I Garcia-Morales, P Del Saz-Orozco, J C Fraile, V F Muñoz
  [show abstract] [hide abstract]
  ABSTRACT: This paper is focused in the design and implementation of a robotic surgical motion controller. The proposed control scheme addresses the issues related to the application of a robot assistant in novel surgical scenario, which combines hand assisted laparoscopic surgery (HALS) with the single incision laparoscopic surgery (SILS) techniques. It is designed for collaborating with the surgeon in a natural way, by performing autonomous movements, in order to assist the surgeon during a surgical maneuver. In this way, it is implemented a hierarchical architecture which includes an upper auto-guide velocity planner connected to a low-level force feedback controller. The first one, based on a behavior approach, computes a collision free trajectory of the surgical instrument tip, held by the robot, for reaching a goal location inside of the abdominal cavity. On the other hand, the force feedback controller uses this trajectory for performing the instrument displacement by taking into account the holonomic movement constraints introduced by the fulcrum point. The aim of this controller is positioning the surgical instrument by minimizing the forces exerted over the abdominal wall due to the fulcrum location uncertainty. The overall system has been integrated in the control architecture of the surgical assistant CISOBOT, designed and developed at the University of Malaga. The whole architecture performance has been tested by means of in vitro trials.
  Computer methods and programs in biomedicine 04/2013;
• Article: On-line prediction of the feeding phase in high-cell density cultivation of rE. coli using constructive neural networks.

  M C Nicoletti, J R Bertini, M M Tanizaki, T C Zangirolami, V M Gonçalves, A C L Horta, R C Giordano
  [show abstract] [hide abstract]
  ABSTRACT: Streptococcus pneumoniae (pneumococcus) is a bacterium responsible for a wide spectrum of illnesses. The surface of the bacterium consists of three distinctive membranes: plasmatic, cellular and the polysaccharide (PS) capsule. PS capsules may mediate several biological processes, particularly invasive infections of human beings. Prevention against pneumococcal related illnesses can be provided by vaccines. There is a sound investment worldwide in the investigation of a proteic antigen as a possible alternative to pneumococcal vaccines based exclusively on PS. A few proteins which are part of the membrane of the pneumococcus seem to have antigen potential to be part of a vaccine, particularly the PspA. A vital aspect in the production of the intended conjugate pneumococcal vaccine is the efficient production (in industrial scale) of both, the chosen PS serotypes as well as the PspA protein. Growing recombinant Escherichia coli (rE. coli) in high-cell density cultures (HCDC) under a fed-batch regime requires a refined continuous control over various process variables where the on-line prediction of the feeding phase is of particular relevance and one of the focuses of this paper. The viability of an on-line monitoring software system, based on constructive neural networks (CoNN), for automatically detecting the time to start the fed-phase of a HCDC of rE. coli that contains a plasmid used for PspA expression is investigated. The paper describes the data and methodology used for training five different types of CoNNs, four of them suitable for classification tasks and one suitable for regression tasks, aiming at comparatively investigate both approaches. Results of software simulations implementing five CoNN algorithms as well as conventional neural networks (FFNN), decision trees (DT) and support vector machines (SVM) are also presented and discussed. A modified CasCor algorithm, implementing a data softening process, has shown to be an efficient candidate to be part of an on-line HCDC monitoring system for detecting the feeding phase of the HCDC process.
  Computer methods and programs in biomedicine 04/2013;
• Article: A new surveillance and spatio-temporal visualization tool SIMID: SIMulation of Infectious Diseases using random networks and GIS.

  Lilia L Ramírez-Ramírez, Yulia R Gel, Mary Thompson, Eileen de Villa, Matt McPherson
  [show abstract] [hide abstract]
  ABSTRACT: In this paper we discuss the SIMID tool for simulation of the spread of infectious disease, enabling spatio-temporal visualization of the dynamics of influenza outbreaks. SIMID is based on modern random network methodology and implemented within the R and GIS frameworks. The key advantage of SIMID is that it allows not only for the construction of a possible scenario for the spread of an infectious disease but also for the assessment of mitigation strategies, variation and uncertainty in disease parameters and randomness in the progression of an outbreak. We illustrate SIMID by application to an influenza epidemic simulation in a population constructed to resemble the Region of Peel, Ontario, Canada.
  Computer methods and programs in biomedicine 04/2013;