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Fulltext National Orthopedic Registry in Malaysia--National Orthopedics Diabetic Hand and Foot Database (NODFD)

Muhammad Anwar Hau A

Med J Malaysia, 2008 Sep;63 Suppl C:75.
PMID: 19230251
Matched MeSH terms: Databases as Topic/organization & administration
Fulltext Annual report of National Orthopaedic Registry Malaysia (NORM) Hip Fracture 2009

Abdullah MAH, Abdullah AT

Citation:
Abdullah MAH, Abdullah AT. Annual report of National Orthopaedic Registry Malaysia (NORM) Hip Fracture 2009. Kuala Lumpur: Clinical Research Centre, Kuala Lumpur; 2010

Matched MeSH terms: Databases as Topic
Fulltext Annual report of National Orthopaedic Registry Malaysia (NORM) Diabetic Foot 2009

Abdullah MAH, Abdullah AT

Citation: Abdullah MAH, Abdullah AT. Annual report of National Orthopaedic Registry Malaysia (NORM) Diabetic Foot 2009. Kuala Lumpur: Clinical Research Centre, Malaysia; 2010

Matched MeSH terms: Databases as Topic
Fulltext Kidney-inspired algorithm with reduced functionality treatment for classification and time series prediction

Jaddi NS, Abdullah S

PLoS One, 2019;14(1):e0208308.
PMID: 30608936 DOI: 10.1371/journal.pone.0208308

Optimization of an artificial neural network model through the use of optimization algorithms is the common method employed to search for an optimum solution for a broad variety of real-world problems. One such optimization algorithm is the kidney-inspired algorithm (KA) which has recently been proposed in the literature. The algorithm mimics the four processes performed by the kidneys: filtration, reabsorption, secretion, and excretion. However, a human with reduced kidney function needs to undergo additional treatment to improve kidney performance. In the medical field, the glomerular filtration rate (GFR) test is used to check the health of kidneys. The test estimates the amount of blood that passes through the glomeruli each minute. In this paper, we mimic this kidney function test and the GFR result is used to select a suitable step to add to the basic KA process. This novel imitation is designed for both minimization and maximization problems. In the proposed method, depends on GFR test result which is less than 15 or falls between 15 and 60 or is more than 60 a particular action is performed. These additional processes are applied as required with the aim of improving exploration of the search space and increasing the likelihood of the KA finding the optimum solution. The proposed method is tested on test functions and its results are compared with those of the basic KA. Its performance on benchmark classification and time series prediction problems is also examined and compared with that of other available methods in the literature. In addition, the proposed method is applied to a real-world water quality prediction problem. The statistical analysis of all these applications showed that the proposed method had a ability to improve the optimization outcome.

Matched MeSH terms: Databases as Topic
Fulltext Question classification based on Bloom's taxonomy cognitive domain using modified TF-IDF and word2vec

Mohammed M, Omar N

PLoS One, 2020;15(3):e0230442.
PMID: 32191738 DOI: 10.1371/journal.pone.0230442

The assessment of examination questions is crucial in educational institutes since examination is one of the most common methods to evaluate students' achievement in specific course. Therefore, there is a crucial need to construct a balanced and high-quality exam, which satisfies different cognitive levels. Thus, many lecturers rely on Bloom's taxonomy cognitive domain, which is a popular framework developed for the purpose of assessing students' intellectual abilities and skills. Several works have been proposed to automatically handle the classification of questions in accordance with Bloom's taxonomy. Most of these works classify questions according to specific domain. As a result, there is a lack of technique of classifying questions that belong to the multi-domain areas. The aim of this paper is to present a classification model to classify exam questions based on Bloom's taxonomy that belong to several areas. This study proposes a method for classifying questions automatically, by extracting two features, TFPOS-IDF and word2vec. The purpose of the first feature was to calculate the term frequency-inverse document frequency based on part of speech, in order to assign a suitable weight for essential words in the question. The second feature, pre-trained word2vec, was used to boost the classification process. Then, the combination of these features was fed into three different classifiers; K-Nearest Neighbour, Logistic Regression, and Support Vector Machine, in order to classify the questions. The experiments used two datasets. The first dataset contained 141 questions, while the other dataset contained 600 questions. The classification result for the first dataset achieved an average of 71.1%, 82.3% and 83.7% weighted F1-measure respectively. The classification result for the second dataset achieved an average of 85.4%, 89.4% and 89.7% weighted F1-measure respectively. The finding from this study showed that the proposed method is significant in classifying questions from multiple domains based on Bloom's taxonomy.

Matched MeSH terms: Databases as Topic
The accuracy of an Online Sequential Extreme Learning Machine in detecting voice pathology using the Malaysian Voice Pathology Database

Za'im NAN, Al-Dhief FT, Azman M, Alsemawi MRM, Abdul Latiff NMA, Mat Baki M

J Otolaryngol Head Neck Surg, 2023 Sep 20;52(1):62.
PMID: 37730624 DOI: 10.1186/s40463-023-00661-6

BACKGROUND: A multidimensional voice quality assessment is recommended for all patients with dysphonia, which requires a patient visit to the otolaryngology clinic. The aim of this study was to determine the accuracy of an online artificial intelligence classifier, the Online Sequential Extreme Learning Machine (OSELM), in detecting voice pathology. In this study, a Malaysian Voice Pathology Database (MVPD), which is the first Malaysian voice database, was created and tested.
METHODS: The study included 382 participants (252 normal voices and 130 dysphonic voices) in the proposed database MVPD. Complete data were obtained for both groups, including voice samples, laryngostroboscopy videos, and acoustic analysis. The diagnoses of patients with dysphonia were obtained. Each voice sample was anonymized using a code that was specific to each individual and stored in the MVPD. These voice samples were used to train and test the proposed OSELM algorithm. The performance of OSELM was evaluated and compared with other classifiers in terms of the accuracy, sensitivity, and specificity of detecting and differentiating dysphonic voices.
RESULTS: The accuracy, sensitivity, and specificity of OSELM in detecting normal and dysphonic voices were 90%, 98%, and 73%, respectively. The classifier differentiated between structural and non-structural vocal fold pathology with accuracy, sensitivity, and specificity of 84%, 89%, and 88%, respectively, while it differentiated between malignant and benign lesions with an accuracy, sensitivity, and specificity of 92%, 100%, and 58%, respectively. Compared to other classifiers, OSELM showed superior accuracy and sensitivity in detecting dysphonic voices, differentiating structural versus non-structural vocal fold pathology, and between malignant and benign voice pathology.
CONCLUSION: The OSELM algorithm exhibited the highest accuracy and sensitivity compared to other classifiers in detecting voice pathology, classifying between malignant and benign lesions, and differentiating between structural and non-structural vocal pathology. Hence, it is a promising artificial intelligence that supports an online application to be used as a screening tool to encourage people to seek medical consultation early for a definitive diagnosis of voice pathology.

Matched MeSH terms: Databases as Topic
Fulltext An invariability-area relationship sheds new light on the spatial scaling of ecological stability

Wang S, Loreau M, Arnoldi JF, Fang J, Rahman KA, Tao S, et al.

Nat Commun, 2017 May 19;8:15211.
PMID: 28524860 DOI: 10.1038/ncomms15211

The spatial scaling of stability is key to understanding ecological sustainability across scales and the sensitivity of ecosystems to habitat destruction. Here we propose the invariability-area relationship (IAR) as a novel approach to investigate the spatial scaling of stability. The shape and slope of IAR are largely determined by patterns of spatial synchrony across scales. When synchrony decays exponentially with distance, IARs exhibit three phases, characterized by steeper increases in invariability at both small and large scales. Such triphasic IARs are observed for primary productivity from plot to continental scales. When synchrony decays as a power law with distance, IARs are quasilinear on a log-log scale. Such quasilinear IARs are observed for North American bird biomass at both species and community levels. The IAR provides a quantitative tool to predict the effects of habitat loss on population and ecosystem stability and to detect regime shifts in spatial ecological systems, which are goals of relevance to conservation and policy.

Matched MeSH terms: Databases as Topic
Fulltext Multistrategy self-organizing map learning for classification problems

Hasan S, Shamsuddin SM

Comput Intell Neurosci, 2011;2011:121787.
PMID: 21876686 DOI: 10.1155/2011/121787

Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test.

Matched MeSH terms: Databases as Topic/statistics & numerical data
Fulltext Can global variation of nasopharynx cancer be retrieved from the combined analyses of IARC Cancer Information (CIN) databases?

Sun X, Tong LP, Wang YT, Wu YX, Sheng HS, Lu LJ, et al.

PLoS One, 2011;6(7):e22039.
PMID: 21760951 DOI: 10.1371/journal.pone.0022039

The international nasopharynx cancer (NPC) burdens are masked due to the lack of integrated studies that examine epidemiological data based on up-to-date international disease databases such as the Cancer Information (CIN) databases provided by the International Agency for Research on Cancer (IARC).

Matched MeSH terms: Databases as Topic*
Fulltext SuCComBase: a manually curated repository of plant sulfur-containing compounds

Harun S, Abdullah-Zawawi MR, A-Rahman MRA, Muhammad NAN, Mohamed-Hussein ZA

Database (Oxford), 2019 01 01;2019.
PMID: 30793170 DOI: 10.1093/database/baz021

Plants produce a wide range of secondary metabolites that play important roles in plant defense and immunity, their interaction with the environment and symbiotic associations. Sulfur-containing compounds (SCCs) are a group of important secondary metabolites produced in members of the Brassicales order. SCCs constitute various groups of phytochemicals, but not much is known about them. Findings from previous studies on SCCs were scattered in published literatures, hence SuCComBase was developed to store all molecular information related to the biosynthesis of SCCs. Information that includes genes, proteins and compounds that are involved in the SCC biosynthetic pathway was manually identified from databases and published scientific literatures. Sets of co-expression data was analyzed to search for other possible (previously unknown) genes that might be involved in the biosynthesis of SCC. These genes were named as potential SCC-related encoding genes. A total of 147 known and 92 putative Arabidopsis thaliana SCC-related genes from literatures were used to identify other potential SCC-related encoding genes. We identified 778 potential SCC-related encoding genes, 4026 homologs to the SCC-related encoding genes and 116 SCCs as shown on SuCComBase homepage. Data entries are searchable from the Main page, Search, Browse and Datasets tabs. Users can easily download all data stored in SuCComBase. All publications related to SCCs are also indexed in SuCComBase, which is currently the first and only database dedicated to plant SCCs. SuCComBase aims to become a manually curated and au fait knowledge-based repository for plant SCCs.

Matched MeSH terms: Databases as Topic*
Fulltext Development of vision based multiview gait recognition system with MMUGait database

Ng H, Tan WH, Abdullah J, Tong HL

ScientificWorldJournal, 2014;2014:376569.
PMID: 25143972 DOI: 10.1155/2014/376569

This paper describes the acquisition setup and development of a new gait database, MMUGait. This database consists of 82 subjects walking under normal condition and 19 subjects walking with 11 covariate factors, which were captured under two views. This paper also proposes a multiview model-based gait recognition system with joint detection approach that performs well under different walking trajectories and covariate factors, which include self-occluded or external occluded silhouettes. In the proposed system, the process begins by enhancing the human silhouette to remove the artifacts. Next, the width and height of the body are obtained. Subsequently, the joint angular trajectories are determined once the body joints are automatically detected. Lastly, crotch height and step-size of the walking subject are determined. The extracted features are smoothened by Gaussian filter to eliminate the effect of outliers. The extracted features are normalized with linear scaling, which is followed by feature selection prior to the classification process. The classification experiments carried out on MMUGait database were benchmarked against the SOTON Small DB from University of Southampton. Results showed correct classification rate above 90% for all the databases. The proposed approach is found to outperform other approaches on SOTON Small DB in most cases.

Matched MeSH terms: Databases as Topic
An oral cancer biobank initiative: a platform for multidisciplinary research in a developing country

Zain RB, Athirajan V, Ghani WM, Razak IA, Raja Latifah RJ, Ismail SM, et al.

Cell Tissue Bank, 2013 Mar;14(1):45-52.
PMID: 22373599 DOI: 10.1007/s10561-012-9298-0

Identification of diagnostic markers for early detection and development of novel and therapeutic agents for effective patient management are the main motivation for cancer research. Biological specimens from large cohort and case-control studies which are crucial in providing successful research outcomes are often the limiting factor that hinders research efforts, especially in developing countries. Therefore, the Malaysian Oral Cancer Database and Tissue Bank System (MOCDTBS) were established to systematically collect large number of samples with comprehensive sociodemographic, clinicopathological, management strategies, quality of life and associated patient follow-up data to facilitate oral cancer research in Malaysia. The MOCDTBS also promotes sharing among researchers and the development of a multidisciplinary research team. The following article aims to describe the process of setting-up and managing the MOCDTBS.

Matched MeSH terms: Databases as Topic
Human behavior state profile mapping based on recalibrated speech affective space model

Kamaruddin N, Wahab A

Annu Int Conf IEEE Eng Med Biol Soc, 2012;2012:2021-4.
PMID: 23366315 DOI: 10.1109/EMBC.2012.6346354

People typically associate health with only physical health. However, health is also interconnected to mental and emotional health. People who are emotionally healthy are in control of their behaviors and experience better quality of life. Hence, understanding human behavior is very important in ensuring the complete understanding of one's holistic health. In this paper, we attempt to map human behavior state (HBS) profiles onto recalibrated speech affective space model (rSASM). Such an approach is derived from hypotheses that: 1) Behavior is influenced by emotion, 2) Emotion can be quantified through speech, 3) Emotion is dynamic and changes over time and 4) the emotion conveyance is conditioned by culture. Empirical results illustrated that the proposed approach can complement other types of behavior analysis in such a way that it offers more explanatory components from the perspective of emotion primitives (valence and arousal). Four different driving HBS; namely: distracted, laughing, sleepy and normal are profiled onto the rSASM to visualize the correlation between HBS and emotion. This approach can be incorporated in the future behavior analysis to envisage better performance.

Matched MeSH terms: Databases as Topic
ConnectViz: Accelerated Approach for Brain Structural Connectivity Using Delaunay Triangulation

Adeshina AM, Hashim R

Interdiscip Sci, 2016 Mar;8(1):53-64.
PMID: 26260066 DOI: 10.1007/s12539-015-0274-9

Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using compute unified device architecture, extending the previously proposed SurLens Visualization and computer aided hepatocellular carcinoma frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, USA. Significantly, our proposed framework is able to generate and extract points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the nodes and the edges. The framework is very efficient in providing greater interactivity as a way of representing the nodes and the edges intuitively, all achieved at a considerably interactive speed for instantaneous mapping of the datasets' features. Uniquely, the connectomic algorithm performed remarkably fast with normal hardware requirement specifications.

Matched MeSH terms: Databases as Topic
Fulltext How does mandibular advancement with or without maxillary procedures affect pharyngeal airways? An overview of systematic reviews

Tan SK, Leung WK, Tang ATH, Zwahlen RA

PLoS One, 2017;12(7):e0181146.
PMID: 28749983 DOI: 10.1371/journal.pone.0181146

BACKGROUND: Mandibular advancement surgery may positively affect pharyngeal airways and therefore potentially beneficial to obstructive sleep apnea (OSA).
OBJECTIVE: To collect evidence from published systematic reviews that have evaluated pharyngeal airway changes related to mandibular advancement with or without maxillary procedures.
METHODOLOGY: PubMed, EMBASE, Web of Science, and Cochrane Library were searched without limiting language or timeline. Eligible systematic reviews evaluating changes in pharyngeal airway dimensions and respiratory parameters after mandibular advancement with or without maxillary surgery were identified and included.
RESULTS: This overview has included eleven systematic reviews. Maxillomandibular advancement (MMA) increases linear, cross-sectional plane and volumetric measurements of pharyngeal airways significantly (p<0.0001), while reducing the apnea-hypopnea index (AHI) and the respiratory disturbance index (RDI) significantly (p<0.0001). Two systematic reviews included primary studies that have evaluated single-jaw mandibular advancement, but did not discuss their effect onto pharyngeal airways. Based on the included primary studies of those systematic reviews, single-jaw mandibular advancement was reported to significantly increase pharyngeal airway dimensions (p<0.05); however, conclusive long-term results were lacking.
CONCLUSION: MMA increases pharyngeal airway dimensions and is beneficial to patients suffering from OSA. However, more evidence is still needed to draw definite conclusion related to the effect of single-jaw mandibular advancement osteotomies on pharyngeal airways.

Matched MeSH terms: Databases as Topic
Fulltext 3-Dimensional facial expression recognition in human using multi-points warping

Agbolade O, Nazri A, Yaakob R, Ghani AA, Cheah YK

BMC Bioinformatics, 2019 Dec 02;20(1):619.
PMID: 31791234 DOI: 10.1186/s12859-019-3153-2

BACKGROUND: Expression in H-sapiens plays a remarkable role when it comes to social communication. The identification of this expression by human beings is relatively easy and accurate. However, achieving the same result in 3D by machine remains a challenge in computer vision. This is due to the current challenges facing facial data acquisition in 3D; such as lack of homology and complex mathematical analysis for facial point digitization. This study proposes facial expression recognition in human with the application of Multi-points Warping for 3D facial landmark by building a template mesh as a reference object. This template mesh is thereby applied to each of the target mesh on Stirling/ESRC and Bosphorus datasets. The semi-landmarks are allowed to slide along tangents to the curves and surfaces until the bending energy between a template and a target form is minimal and localization error is assessed using Procrustes ANOVA. By using Principal Component Analysis (PCA) for feature selection, classification is done using Linear Discriminant Analysis (LDA).
RESULT: The localization error is validated on the two datasets with superior performance over the state-of-the-art methods and variation in the expression is visualized using Principal Components (PCs). The deformations show various expression regions in the faces. The results indicate that Sad expression has the lowest recognition accuracy on both datasets. The classifier achieved a recognition accuracy of 99.58 and 99.32% on Stirling/ESRC and Bosphorus, respectively.
CONCLUSION: The results demonstrate that the method is robust and in agreement with the state-of-the-art results.

Matched MeSH terms: Databases as Topic
Fulltext Malaysian Cardiothoracic Surgery Registry--a patient registry to evaluate the health outcomes of patients undergoing surgery for cardiothoracic diseases in Malaysia

Anas R, Rahman I, Jahizah H, Hassan A, Ezani T, Jong YH, et al.

Med J Malaysia, 2008 Sep;63 Suppl C:78-80.
PMID: 19227680

The formulation of the Cardiothoracic Registry. Cardiothoracic surgery is the field of medicine involved in surgical treatment of diseases affecting organs inside the thorax (the chest). It is a general treatment of conditions of the heart (heart disease) and lungs (lung disease). In Malaysia, due to lack of data collection we do not have estimates of number and outcome of such procedure in the country. Western figures are often used as our reference values and this may not accurately reflect our Malaysian population. The Malaysian Cardiothoracic Surgery Registry (MyCARE) by the Ministry of Health will be a valuable tool to provide timely and robust data of cardiology practice, its safety and cost effectiveness and most importantly the outcome of these patients in the Malaysian setting.

Matched MeSH terms: Databases as Topic/organization & administration
Computational Analysis and In silico Predictive Modeling for Inhibitors of PhoP Regulon in S. typhi on High-Throughput Screening Bioassay Dataset

Kaur H, Ahmad M, Scaria V

Interdiscip Sci, 2016 Mar;8(1):95-101.
PMID: 26298582 DOI: 10.1007/s12539-015-0273-x

There is emergence of multidrug-resistant Salmonella enterica serotype typhi in pandemic proportions throughout the world, and therefore, there is a necessity to speed up the discovery of novel molecules having different modes of action and also less influenced by the resistance formation that would be used as drug for the treatment of salmonellosis particularly typhoid fever. The PhoP regulon is well studied and has now been shown to be a critical regulator of number of gene expressions which are required for intracellular survival of S. enterica and pathophysiology of disease like typhoid. The evident roles of two-component PhoP-/PhoQ-regulated products in salmonella virulence have motivated attempts to target them therapeutically. Although the discovery process of biologically active compounds for the treatment of typhoid relies on hit-finding procedure, using high-throughput screening technology alone is very expensive, as well as time consuming when performed on large scales. With the recent advancement in combinatorial chemistry and contemporary technique for compounds synthesis, there are more and more compounds available which give ample growth of diverse compound library, but the time and endeavor required to screen these unfocused massive and diverse library have been slightly reduced in the past years. Hence, there is demand to improve the high-quality hits and success rate for high-throughput screening that required focused and biased compound library toward the particular target. Therefore, we still need an advantageous and expedient method to prioritize the molecules that will be utilized for biological screens, which saves time and is also inexpensive. In this concept, in silico methods like machine learning are widely applicable technique used to build computational model for high-throughput virtual screens to prioritize molecules for advance study. Furthermore, in computational analysis, we extended our study to identify the common enriched structural entities among the biologically active compound toward finding out the privileged scaffold.

Matched MeSH terms: Databases as Topic*
Fulltext Development and validation of a risk model for predicting adverse drug reactions in older people during hospital stay: Brighton Adverse Drug Reactions Risk (BADRI) model

Tangiisuran B, Scutt G, Stevenson J, Wright J, Onder G, Petrovic M, et al.

PLoS One, 2014;9(10):e111254.
PMID: 25356898 DOI: 10.1371/journal.pone.0111254

Older patients are at an increased risk of developing adverse drug reactions (ADR). Of particular concern are the oldest old, which constitute an increasingly growing population. Having a validated clinical tool to identify those older patients at risk of developing an ADR during hospital stay would enable healthcare staff to put measures in place to reduce the risk of such an event developing. The current study aimed to (1) develop and (2) validate an ADR risk prediction model.

Matched MeSH terms: Databases as Topic
The impact of case reports in oral and maxillofacial surgery

Nabil S, Samman N

Int J Oral Maxillofac Surg, 2012 Jul;41(7):789-96.
PMID: 22516439 DOI: 10.1016/j.ijom.2012.03.007

This review examines the effect of publishing case reports on journal impact factor and future research. All case reports published in the four major English language oral and maxillofacial surgery journals in the two year period, 2007-2008, were searched manually. The citation data of each case report were retrieved from the ISI online database. The number, percentage and mean citations received by case reports and their relation to the 2009 journal impact factor were analysed. Case reports which received more than 5 citations were also identified and all of the citing articles retrieved and analysed. Thirty-one percent of all articles published in major oral and maxillofacial journals in 2007-2008 were case reports. Case reports had a low citation rate with a mean citation of less than 1. There were 38 (7.2%) case reports with more than 5 citations and 30% of the citing articles were also case reports. The publication of case reports negatively affected journal impact factor which correlated directly with the percentage of case reports published within a journal. Case reports reporting recent topics, describing new treatment/diagnosis method and with a literature review were more likely to receive citations.

Matched MeSH terms: Databases as Topic

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