Displaying publications 1 - 20 of 77 in total

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  1. Pasquariella SK
    POPIN Bull, 1984 Dec.
    PMID: 12267287
    Matched MeSH terms: Information Storage and Retrieval*
  2. Abidi SS
    PMID: 10724926
    Presently, there is a growing demand from the healthcare community to leverage upon and transform the vast quantities of healthcare data into value-added, 'decision-quality' knowledge, vis-à-vis, strategic knowledge services oriented towards healthcare management and planning. To meet this end, we present a Strategic Knowledge Services Info-structure that leverages on existing healthcare knowledge/data bases to derive decision-quality knowledge-knowledge that is extracted from healthcare data through services akin to knowledge discovery in databases and data mining.
    Matched MeSH terms: Information Storage and Retrieval/statistics & numerical data*
  3. Fozi K, Teng CL, Krishnan R, Shajahan Y
    Med J Malaysia, 2000 Dec;55(4):486-92.
    PMID: 11221162
    This is a prospective study of clinical questions generated in primary care consultations and a comparison of two approaches to answering those clinical questions. Twenty-one doctors in a university-based primary care clinic submitted 78 clinical questions arising from patient consultations during 24 clinic days (0.01 question per patient encounter). These doctors subsequently found answers to 40% of their questions but were satisfied with only 67% of these answers. The investigators were able to provide answers for 95% of the questions asked and the doctors rated these answers as satisfactory in 86% of instances. Answers obtained by investigators had significantly higher satisfaction score than those obtained by doctors' search (p = 0.002). The two main findings of this study are (1) almost all questions arising in clinic setting could be answered by intensive search; (2) answers found by intensive searches were judged to be more satisfactory than those found routinely by doctors. Provision of an information retrieval service in addition to training in the searching and appraisal of medical literature are possible solutions to the information needs of busy clinicians.

    Study site: Primary Care Clinic,
    University Hospital Kuala Lumpur i
    Matched MeSH terms: Information Storage and Retrieval/standards*
  4. Zaidi SZ, Abidi SS, Manickam S
    PMID: 15460713
    This paper presents a case for an intelligent agent based framework for knowledge discovery in a distributed healthcare environment comprising multiple heterogeneous healthcare data repositories. Data-mediated knowledge discovery, especially from multiple heterogeneous data resources, is a tedious process and imposes significant operational constraints on end-users. We demonstrate that autonomous, reactive and proactive intelligent agents provide an opportunity to generate end-user oriented, packaged, value-added decision-support/strategic planning services for healthcare professionals, manages and policy makers, without the need for a priori technical knowledge. Since effective healthcare is grounded in good communication, experience sharing, continuous learning and proactive actions, we use intelligent agents to implement an Agent based Data Mining Infostructure that provides a suite of healthcare-oriented decision-support/strategic planning services.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  5. Saffor A, bin Ramli AR, Ng KH
    Australas Phys Eng Sci Med, 2003 Jun;26(2):39-44.
    PMID: 12956184
    Wavelet-based image coding algorithms (lossy and lossless) use a fixed perfect reconstruction filter-bank built into the algorithm for coding and decoding of images. However, no systematic study has been performed to evaluate the coding performance of wavelet filters on medical images. We evaluated the best types of filters suitable for medical images in providing low bit rate and low computational complexity. In this study a variety of wavelet filters are used to compress and decompress computed tomography (CT) brain and abdomen images. We applied two-dimensional wavelet decomposition, quantization and reconstruction using several families of filter banks to a set of CT images. Discreet Wavelet Transform (DWT), which provides efficient framework of multi-resolution frequency was used. Compression was accomplished by applying threshold values to the wavelet coefficients. The statistical indices such as mean square error (MSE), maximum absolute error (MAE) and peak signal-to-noise ratio (PSNR) were used to quantify the effect of wavelet compression of selected images. The code was written using the wavelet and image processing toolbox of the MATLAB (version 6.1). This results show that no specific wavelet filter performs uniformly better than others except for the case of Daubechies and bi-orthogonal filters which are the best among all. MAE values achieved by these filters were 5 x 10(-14) to 12 x 10(-14) for both CT brain and abdomen images at different decomposition levels. This indicated that using these filters a very small error (approximately 7 x 10(-14)) can be achieved between original and the filtered image. The PSNR values obtained were higher for the brain than the abdomen images. For both the lossy and lossless compression, the 'most appropriate' wavelet filter should be chosen adaptively depending on the statistical properties of the image being coded to achieve higher compression ratio.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  6. College of Pathologists, Academy of Medicine of Malaysia, Ministry of Health Malaysia
    Malays J Pathol, 2005 Jun;27(1):51-6.
    PMID: 16676694
    Matched MeSH terms: Information Storage and Retrieval/standards*
  7. Firdaus Raih M, Ahmad HA, Sharum MY, Azizi N, Mohamed R
    Appl. Bioinformatics, 2005;4(2):147-50.
    PMID: 16128617
    Bacterial proteases are an important group of enzymes that have very diverse biochemical and cellular functions. Proteases from prokaryotic sources also have a wide range of uses, either in medicine as pathogenic factors or in industry and therapeutics. ProLysED (Prokaryotic Lysis Enzymes Database), our meta-server integrated database of bacterial proteases, is a useful, albeit very niche, resource. The features include protease classification browsing and searching, organism-specific protease browsing, molecular information and visualisation of protease structures from the Protein Data Bank (PDB) as well as predicted protease structures.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  8. Khuan LY, Bister M, Blanchfield P, Salleh YM, Ali RA, Chan TH
    Australas Phys Eng Sci Med, 2006 Jun;29(2):216-28.
    PMID: 16845928
    Increased inter-equipment connectivity coupled with advances in Web technology allows ever escalating amounts of physiological data to be produced, far too much to be displayed adequately on a single computer screen. The consequence is that large quantities of insignificant data will be transmitted and reviewed. This carries an increased risk of overlooking vitally important transients. This paper describes a technique to provide an integrated solution based on a single algorithm for the efficient analysis, compression and remote display of long-term physiological signals with infrequent short duration, yet vital events, to effect a reduction in data transmission and display cluttering and to facilitate reliable data interpretation. The algorithm analyses data at the server end and flags significant events. It produces a compressed version of the signal at a lower resolution that can be satisfactorily viewed in a single screen width. This reduced set of data is initially transmitted together with a set of 'flags' indicating where significant events occur. Subsequent transmissions need only involve transmission of flagged data segments of interest at the required resolution. Efficient processing and code protection with decomposition alone is novel. The fixed transmission length method ensures clutter-less display, irrespective of the data length. The flagging of annotated events in arterial oxygen saturation, electroencephalogram and electrocardiogram illustrates the generic property of the algorithm. Data reduction of 87% to 99% and improved displays are demonstrated.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  9. Zain JM, Fauzi AM, Aziz AA
    Conf Proc IEEE Eng Med Biol Soc, 2007 10 20;2006:5459-62.
    PMID: 17946306
    Digital watermarking medical images provides security to the images. The purpose of this study was to see whether digitally watermarked images changed clinical diagnoses when assessed by radiologists. We embedded 256 bits watermark to various medical images in the region of non-interest (RONI) and 480K bits in both region of interest (ROI) and RONI. Our results showed that watermarking medical images did not alter clinical diagnoses. In addition, there was no difference in image quality when visually assessed by the medical radiologists. We therefore concluded that digital watermarking medical images were safe in terms of preserving image quality for clinical purposes.
    Matched MeSH terms: Information Storage and Retrieval
  10. Nugroho H, Fadzil MH, Yap VV, Norashikin S, Suraiya HH
    PMID: 18002737
    In this paper, we describe an image processing scheme to analyze and determine areas of skin that have undergone repigmentation in particular, during the treatment of vitiligo. In vitiligo cases, areas of skin become pale or white due to the lack of skin pigment called melanin. Vitiligo treatment causes skin repigmentation resulting in a normal skin color. However, it is difficult to determine and quantify the amount of repigmentation visually during treatment because the repigmentation progress is slow and moreover changes in skin color can only be discerned over a longer time frame typically 6 months. Here, we develop a digital image analysis scheme that can identify and determine vitiligo skin areas and repigmentation progression on a shorter time period. The technique is based on principal component analysis and independent component analysis which converts the RGB skin image into a skin image that represent skin areas due to melanin and haemoglobin only, followed by segmentation process. Vitiligo skin lesions are identified as skin areas that lack melanin (non-melanin areas). In the initial studies of 4 patients, the method has been able to quantify repigmentation in vitiligo lesion. Hence it is now possible to determine repigmentation progression objectively and treatment efficacy on a shorter time cycle.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  11. Zain JM, Fauzi AR
    PMID: 18003297
    This paper will study and evaluate watermarking technique by Zain and Fauzi [1]. Recommendations will then be made to enhance the technique especially in the aspect of recovery or reconstruction rate for medical images. A proposal will also be made for a better distribution of watermark to minimize the distortion of the Region of Interest (ROI). The final proposal will enhance AW-TDR in three aspects; firstly the image quality in the ROI will be improved as the maximum change is only 2 bits in every 4 pixels, or embedding rate of 0.5 bits/pixel. Secondly the recovery rate will also be better since the recovery bits are located outside the region of interest. The disadvantage in this is that, only manipulation done in the ROI will be detected. Thirdly the quality of the reconstructed image will be enhanced since the average of 2 x 2 pixels would be used to reconstruct the tampered image.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  12. Othman RM, Deris S, Illias RM
    J Biomed Inform, 2008 Feb;41(1):65-81.
    PMID: 17681495
    A genetic similarity algorithm is introduced in this study to find a group of semantically similar Gene Ontology terms. The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. The semantic similarity measure algorithm is used to compute the similitude strength between the Gene Ontology terms. Then, the parallel genetic algorithm is employed to perform batch retrieval and to accelerate the search in large search space of the Gene Ontology graph. The genetic similarity algorithm is implemented in the Gene Ontology browser named basic UTMGO to overcome the weaknesses of the existing Gene Ontology browsers which use a conventional approach based on keyword matching. To show the applicability of the basic UTMGO, we extend its structure to develop a Gene Ontology -based protein sequence annotation tool named extended UTMGO. The objective of developing the extended UTMGO is to provide a simple and practical tool that is capable of producing better results and requires a reasonable amount of running time with low computing cost specifically for offline usage. The computational results and comparison with other related tools are presented to show the effectiveness of the proposed algorithm and tools.
    Matched MeSH terms: Information Storage and Retrieval/methods
  13. Kamel NS, Sayeed S, Ellis GA
    IEEE Trans Pattern Anal Mach Intell, 2008 Jun;30(6):1109-13.
    PMID: 18421114 DOI: 10.1109/TPAMI.2008.32
    Utilizing the multiple degrees of freedom offered by the data glove for each finger and the hand, a novel on-line signature verification system using the Singular Value Decomposition (SVD) numerical tool for signature classification and verification is presented. The proposed technique is based on the Singular Value Decomposition in finding r singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, so the effective dimensionality of A can be reduced. Having modeled the data glove signature through its r-principal subspace, signature authentication is performed by finding the angles between the different subspaces. A demonstration of the data glove is presented as an effective high-bandwidth data entry device for signature verification. This SVD-based signature verification technique is tested and its performance is shown to be able to recognize forgery signatures with a false acceptance rate of less than 1.2%.
    Matched MeSH terms: Information Storage and Retrieval/methods
  14. Mueen A, Zainuddin R, Baba MS
    J Digit Imaging, 2008 Sep;21(3):290-5.
    PMID: 17846834
    Image retrieval at the semantic level mostly depends on image annotation or image classification. Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. To address first issue, multilevel features are extracted to construct the feature vector, which represents the contents of the image. To address second issue, domain-dependent concept hierarchy is constructed for interpretation of image semantic concepts. To address third issue, automatic multilevel code generation is proposed for image classification and multilevel image annotation. We make use of the existing image annotation to address second and third issues. Our experiments on a specific domain of X-ray images have given encouraging results.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  15. Patrick TH, Fong AY, Sebastian Y, Raman V, Wong YH, Sim KH
    Inform Health Soc Care, 2009 Jan;34(1):1-9.
    PMID: 19306194 DOI: 10.1080/17538150902773090
    Mining for medical data poses different challenges compared with mining other types of data. The wide range of imaging modalities of medical data leads to data integration and compatibility issues. The analysis of imaging modalities is further complicated by the different format and attributes used by the different imaging equipment by different vendors. Human factors such as interest of adapting data mining into diagnosis and planning process raised the difficulty of engaging the users into the development of a practical and useful data miner. Requirement engineering technique prototyping further enhanced the engagement of users towards the data-miner. Data from different equipment and different vendors are also merged for efficient data analysis and subsequently charting and reporting. We have also successfully engaged the medical doctors into believing the data miner's capability after they reviewed and walkthrough the prototype.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  16. Nalliah S, Chan SL, Ong CL, Suthan TH, Tan KC, She VN, et al.
    Singapore Med J, 2010 Apr;51(4):332-8.
    PMID: 20505913
    Internet search has been the main source for information and data mining in medical research. Its use by medical students has immensely contributed to learning activities. The main aim of the study was to determine the effectiveness of internet use by medical students during their initial years of clinical instruction in order to establish a diagnosis after being provided with the history and physical findings of a clinical problem.
    Matched MeSH terms: Information Storage and Retrieval
  17. Mueen A, Zainuddin R, Baba MS
    J Med Syst, 2010 Oct;34(5):859-64.
    PMID: 20703623 DOI: 10.1007/s10916-009-9300-y
    The next generation of medical information system will integrate multimedia data to assist physicians in clinical decision-making, diagnoses, teaching, and research. This paper describes MIARS (Medical Image Annotation and Retrieval System). MIARS not only provides automatic annotation, but also supports text based as well as image based retrieval strategies, which play important roles in medical training, research, and diagnostics. The system utilizes three trained classifiers, which are trained using training images. The goal of these classifiers is to provide multi-level automatic annotation. Another main purpose of the MIARS system is to study image semantic retrieval strategy by which images can be retrieved according to different levels of annotation.
    Matched MeSH terms: Information Storage and Retrieval*
  18. Ng KH, Peh WC
    Singapore Med J, 2010 Oct;51(10):757-60; quiz 761.
    PMID: 21103809
    A bibliographic database is an organised digital collection of references to published literature. A bibliographic database may be general in scope or may cover a specific academic discipline. There are many types of medical and general bibliographic databases. They cover biomedical and scientific literature, morbidity and mortality statistics, therapeutic regimens, medical records, images and reviews of evidence-based medicine. Getting to know these databases will help researchers and authors to enhance their writing and publishing endeavours.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  19. Hassan A, Ibrahim F
    J Digit Imaging, 2011 Apr;24(2):308-13.
    PMID: 20386951 DOI: 10.1007/s10278-010-9283-8
    This paper presents the development of kidney TeleUltrasound consultation system. The TeleUltrasound system provides an innovative design that aids the acquisition, archiving, and dissemination of medical data and information over the internet as its backbone. The system provides data sharing to allow remote collaboration, viewing, consultation, and diagnosis of medical data. The design is layered upon a standard known as Digital Imaging and Communication in Medicine (DICOM). The DICOM standard defines protocols for exchanging medical images and their associated data. The TeleUltrasound system is an integrated solution for retrieving, processing, and archiving images and providing data storage management using Structured Query Language (SQL) database. Creating a web-based interface is an additional advantage to achieve global accessibility of experts that will widely open the opportunity of greater examination and multiple consultations. This system is equipped with a high level of data security and its performance has been tested with white, black, and gray box techniques. And the result was satisfactory. The overall system has been evaluated by several radiologists in Malaysia, United Arab Emirates, and Sudan, the result is shown within this paper.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  20. Seng WC, Mirisaee SH
    J Med Syst, 2011 Aug;35(4):571-8.
    PMID: 20703533 DOI: 10.1007/s10916-009-9393-3
    Content-based image retrieval techniques have been extensively studied for the past few years. With the growth of digital medical image databases, the demand for content-based analysis and retrieval tools has been increasing remarkably. Blood cell image is a key diagnostic tool for hematologists. An automated system that can retrieved relevant blood cell images correctly and efficiently would save the effort and time of hematologists. The purpose of this work is to develop such a content-based image retrieval system. Global color histogram and wavelet-based methods are used in the prototype. The system allows users to search by providing a query image and select one of four implemented methods. The obtained results demonstrate the proposed extended query refinement has the potential to capture a user's high level query and perception subjectivity by dynamically giving better query combinations. Color-based methods performed better than wavelet-based methods with regard to precision, recall rate and retrieval time. Shape and density of blood cells are suggested as measurements for future improvement. The system developed is useful for undergraduate education.
    Matched MeSH terms: Information Storage and Retrieval/methods*
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