Sri Lanka Journal of Bio-medical Informatics最新文献

{"title":"Customising DHIS2 for Maternal and Child Health Information Management in Sri Lanka","authors":"M. Manoj","doi":"10.4038/SLJBMI.V3I2.2496","DOIUrl":"https://doi.org/10.4038/SLJBMI.V3I2.2496","url":null,"abstract":"Maternal and Child Health (MCH) is an important component of the primary health care system. MCH systems are developed incorporated with health information systems. Electronic MCH Information Management Systems are emerging and they have proven to improve the quality, efficiency and the cost of medical care. Vendor neutral open source software, such as DHIS2, provides the resources to develop most of the Health Information Management systems. By following open standards; quality, productivity, cost management and data safety can be improved. DOi: http://dx.doi.org/10.4038/sljbmi.v3i2.2496 Sri Lanka Journal of Biomedical Informatics 2012; 3 :47-54","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115145993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"eHealth in Public Health Services","authors":"V. Dissanayake","doi":"10.4038/SLJBMI.V3I2.5224","DOIUrl":"https://doi.org/10.4038/SLJBMI.V3I2.5224","url":null,"abstract":"This is the Editorial DOi: http://dx.doi.org/10.4038/sljbmi.v3i2.5224 Sri Lanka Journal of Biomedical Informatics 2012; 3 :32-33","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130487019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"\"e-Praja Suwa Arunalu\": A Pilot Study of a Health Information Management System for Public Health Midwives in Sri Lanka","authors":"E. Shan S. Rodrigo, Samantha Wimalaratne, R. Marasinghe, S. Edirippulige","doi":"10.4038/SLJBMI.V3I2.4737","DOIUrl":"https://doi.org/10.4038/SLJBMI.V3I2.4737","url":null,"abstract":"We conducted a needs analysis amongst 16 Public Health Midwives (PHMs) in Sri Lanka and found that they spend most of their time on managing health records. We developed an electronic Health Information Management System (HIMS) to help them with their work. The HIMS was designed so that it could accept data from the PHMs, and generate reports which could be used by the PHMs themselves as well as by their supervisors. The HIMS was tested by a group of 16 PHMs in a remote area in the Rathnapura district.  Mini-laptops with the software were distributed to the PHMs and they were given the necessary training. They started entering historical data from the registers into the system by themselves. Nearly 10,000 public health records were generated in the first three months. In a subsequent survey, all the PHMs gave positive answers indicating that they were happy with the pilot project and that they would like to continue using it to enhance their service. The system seems to be a practical solution for the field activities of PHMs in Sri Lanka. The knowledge gained from this study would be useful for future e-Health implementations in the public health sector of Sri Lanka. DOi: http://dx.doi.org/10.4038/sljbmi.v3i2.4737 Sri Lanka Journal of Biomedical Informatics 2012; 3 :40-46","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131542774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-wide haplotype analysis","authors":"V. Weerasekara","doi":"10.4038/SLJBMI.V3I1.2564","DOIUrl":"https://doi.org/10.4038/SLJBMI.V3I1.2564","url":null,"abstract":"This literature review was done with the objective of reviewing the genome-wide haplotype analyses which have been already carried out globally. After the completion of the human genome project, several studies on haplotype analysis on various aspects have been published. Such knowledge may provide valuable information on human evolutionary history and lead to indentify genetic variants which that are responsible to occurrence of various diseases.  In addition to the review on International HapMap project, this review emphasizes on the current understanding of the haplotype structure, diversity and distribution of haplotypes, as well as current understanding on linkage disequilibrium with its relationship to the haplotypes. It further reviews the tools available for haplotype analysis with their statistical applicability. Sri Lanka Journal of Bio-Medical Informatics 2012; 3 (1):20-24 DOI: http://dx.doi.org/10.4038/sljbmi.v3i1.2564","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114477054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-wide SNP discovery in associating with human diseases phenotypes","authors":"P.H.C. Kumanayake","doi":"10.4038/SLJBMI.V3I1.2451","DOIUrl":"https://doi.org/10.4038/SLJBMI.V3I1.2451","url":null,"abstract":"Single Nucleotide Polymorphisms or SNPs are a most abundant, stable and simple base pair changes that occur in the genome. It is an important variation that can be used to describe many unsolved problems in modern medicine such as individual variation to disease response, differences in response to treatment, allergies to drug treatment, etc. Monogenic Mendalian diseases are very rear and most of the time the disease has complex multi-genetic involvement. With the advancement of sequencing technologies SNP discovery is becoming fast, accurate and less expensive. As a result the availability of SNP data has become more abundant and is used to create SNPmap and SNPprofile. This SNP map and SNP profile helps to locate the genes that involve some complex diseases like diabetes, vascular diseases, and mental disorders and to describe individual variation in response to treatment as well as finding a drug target in pharmacogenomics. With such developments in Bio-informatics, the dream of “individualized treatment” is becoming a reality. Sri Lanka Journal of Bio-Medical Informatics 2012; 3 (1):25-31 DOI: http://dx.doi.org/10.4038/sljbmi.v3i1.2451","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131490618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of segmental duplications in the human genome","authors":"A. Fonseka","doi":"10.4038/SLJBMI.V3I1.2467","DOIUrl":"https://doi.org/10.4038/SLJBMI.V3I1.2467","url":null,"abstract":"Sequencing the human genome early in this decade marked one of the greatest achievements in the advancement in to science. Soon it opened up a great opportunity to the scientific community worldwide with a massive amount of biological data to be explored. Segmental duplication is one of the structural variations found in the genome sequence. It counts for about 5% of genome and with relatively long segments of sequence of more than 1KB in length and more than 90% of sequence identity. Segmental duplications are distributed within the chromosome and throughout the genome and mostly denced in the subtelometric and pericentrometric regions. Segmental duplications play major rule in the evolutionary history and its association with genetic disorders. This review intends to explore in to the publications on previous studies and to tools and methodology they followed to achieve of their objective of identifying segmental duplications. Finding the similar sequences was done by local sequence alignment algorithms, most frequently with Blast program followed by global alignment algorithms. Further some other tools such as Blat, DupMasker and MUMmer also were being used. Sri Lanka Journal of Bio-Medical Informatics 2012; 3 (1):12-19 DOI: http://dx.doi.org/10.4038/sljbmi.v3i1.2467","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123006635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics in Sri Lanka – Still in its infancy","authors":"V. Dissanayake","doi":"10.4038/SLJBMI.V3I1.5072","DOIUrl":"https://doi.org/10.4038/SLJBMI.V3I1.5072","url":null,"abstract":"This is the Editorial Sri Lanka Journal of Bio-Medical Informatics 2012; 3 (1):1 DOI: http://dx.doi.org/10.4038/sljbmi.v3i1.5072","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129706124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular biological databases: evolutionary history, data modeling, implementation and ethical background","authors":"M. Cooray","doi":"10.4038/SLJBMI.V3I1.2489","DOIUrl":"https://doi.org/10.4038/SLJBMI.V3I1.2489","url":null,"abstract":"Influence from the rapidly growing fields of computer and information sciences in early 1970s was one of the major factors leading to the development of computer based repositories for biological data. Since the emergence of the first ever computer based molecular biological database ‘Protein Data Bank’ in 1971, biological database domain has grown rapidly in the areas of information content and volume, database modeling, implementation and integration. Key driving forces of this growth are: the amount and diversity of data generated from advancing biological research technologies, the challenges imposed on data modeling by the inherent properties of biological data and the concept of  ‘Electronic Data Publishing’ introduced in early 1990s. According to the database release of ‘Nucleic Acid Research’ in 2010, biological database number increased in about 5% during the year of 2009-2010 and in major databases like ‘GenBank’ data volume doubles approximately every 18 months. Due to the data modeling challenges driven by inherent properties of biological data, multiple modeling tools such as ‘Enhanced Entity Relationship’ diagrams and ‘Unified Modeling Language’ are used to model biological mini worlds. To be compatible with diverse data models, multiple implementation approaches are also used by the biological database developers, namely ‘Flat files’ , ‘XML’ , ‘Relational databases’ , ‘Object oriented databases’ , ‘ASN.1’ and etc. Adherence to simplicity and conservative technology provides a better practical approach to biological database modeling and implementation. Even though the biological databases differ in their internal data model, implementation approach and biological scope, almost all of them share similar 3 tier web architecture. This similarity is the basis of the current three major strategies used for database integration namely ‘Link/hypertext integration’ , ‘View integration’ and ‘Data warehousing’ . Ethical framework governing the molecular biological research and databases, need to be re-engineered to accommodate the demands imposed by this rapidly growing scientific field. Sri Lanka Journal of Bio-Medical informatics 2012; 3 (1):2-11 DOI: http://dx.doi.org/10.4038/sljbmi.v3i1.2489","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130993715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Telemedicine today: can late adopters leapfrog!","authors":"R. Marasinghe","doi":"10.4038/SLJBMI.V2I4.4314","DOIUrl":"https://doi.org/10.4038/SLJBMI.V2I4.4314","url":null,"abstract":"Telemedicine (ie. the use of telecommunication and information technologies to provide medical care at a distance), has now grown to a considerable extent with the rapid expansion of mHealth (ie. practice of telemedicine using mobile devices). Telemedicine practices from simple activities such as booking of appointments (1) to more complex activities such as performing surgeries in the outer space (2) . Although, mHealth was initially developed in industrialised countries, it has gained attention in less industrialised countries as well. This development was mainly facilitated by the rapid rise of mobile phone penetration in developing/low-income countries. However, for a sustainable system, integration of technologies per se is not enough. Instead, there should be a wider contribution for its management including identification of telehealth policies and practices.","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127384151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiology Predictor: Cardiology Interpretations for Medical Diagnosis","authors":"Dinithi Nallaperuma, K. Lokuge","doi":"10.4038/SLJBMI.V2I4.2249","DOIUrl":"https://doi.org/10.4038/SLJBMI.V2I4.2249","url":null,"abstract":"Diagnosis of a heart disease is complex. Aspects such as clinical details, blood pressure, pulse rate, cholesterol level and blood test reports, and even patient‟s history, gender and age all are important when diagnosing cardiovascular disease. Interpretation of an Elector Cardiogram (ECG) is one of a key skill developed by cardiologists. Difficulties in analysing complicated ECG may lead to inaccurate diagnosis thus affecting the accuracy and quality with the diagnosis of cardiovascular disease especially among novice. “Cardiology Predictor” is a software system which is capable of assisting medical practitioners to diagnose cardiovascular diseases accurately. The inputs to the system would be ECG and other cardiac factors which would be processed to provide an output of the possible cardiovascular disease. To ensure accuracy and efficiency, ECG signals are used with digital signal processing for decrypting and feature extracting. Furthermore, artificial intelligence is used to diagnose cardiovascular diseases due to the complexity embedded into it. Therefore, an Artificial Neural Network was used to predict cardiovascular disease. The average success rate of the system was 85.6% based on the user evaluation. Domain experts such as cardiologists suggested that the system is most suitable for the emergency room where expert knowledge was not readily available. DOI: http://dx.doi.org/10.4038/sljbmi.v2i4.2249","PeriodicalId":129773,"journal":{"name":"Sri Lanka Journal of Bio-medical Informatics","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128515608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}