The goal of consensus clustering methods is to find a consensus partition that optimally summarizes an ensemble and improves the quality of clustering compared with single clustering algorithms. In this paper, an enhanced voting-based consensus method was introduced and compared with other consensus clustering methods, including co-association-based, graph-based, and voting-based consensus methods. The MDDR and MUV data sets were used for the experiments and were represented by three 2D fingerprints: ALOGP, ECFP_4, and ECFC_4. The results were evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster using four criteria: F-measure, Quality Partition Index (QPI), Rand Index (RI), and Fowlkes-Mallows Index (FMI). The experiments suggest that the consensus methods can deliver significant improvements for the effectiveness of chemical structures clustering.
Initiatives in healthcare knowledge management have provided some interesting solutions for the implementation of large-scale information repositories vis-à-vis the implementation of Healthcare Enterprise Memories (HEM). In this paper, we present an agent-based Intelligent Healthcare Information Assistant (IHIA) for dynamic information gathering, filtering and adaptation from a HEM comprising an amalgamation of (i) databases storing empirical knowledge, (ii) case-bases storing experiential knowledge, (iii) scenario-bases storing tacit knowledge and (iv) document-bases storing explicit knowledge. The featured work leverages intelligent agents and medical ontologies for autonomous HEM-wide navigation, approximate content matching, inter- and intra-repositories content correlation and information adaptation to meet the user's information request. We anticipate that the use of IHIA will empower healthcare stakeholders to actively communicate with an 'information/knowledge-rich' HEM and will be able to retrieve with ease 'useful' task-specific information via the presentation of cognitively intuitive queries.
Health Informatics (HI) has become a world wide issue since 2005 when the WHO Health Metrics Network (HMN) was formed to encourage all of the developing countries (151) to get started in eHealth. Prior to this HMN initiative the only countries with HI in place were the developed countries (40) and a few developing countries (Jamaica, Malaysia, etc.) that were just getting started in HI with a very limited number of applications compared to the developed countries. This paper suggests that much of the experience in HI gained in the developed countries can be shared with the developing countries as 'lessons learnt' - as long as the issue of economics is kept front and foremost in the planning.
Matched MeSH terms: Medical Informatics/economics*
OBJECTIVE: The objective of this survey was to obtain a self-reported assessment of the use of Information and Communication Technology (ICT) by medical students at the International Medical University, Malaysia.
MATERIALS AND METHODS: Students' perceived skills and extent of usage of ICT were evaluated using a questionnaire. Chi-square analysis were performed to ascertain the association between variables. Further statistical testing using Chi-square test for trend was done when one of the variables was ordered, and Spearman rank correlation when both variables were ordered.
RESULTS: Overall, (98%) of students responded to the questionnaire. Twenty seven students (5.7%) did not use a computer either in the university or at home. Most students surveyed reported adequate skills at word processing (55%), e-mailing (78%) and surfing the internet (67%).
CONCLUSION: The results suggests that in order to increase the level of computer literacy among medical students, positive steps would need to be taken, for example the formal inclusion of ICT instruction in the teaching of undergraduate medicine. This will enhance medical students' ability to acquire, appraise, and use information in order to solve clinical and other problems quickly and efficiently in the course of their studies, and more importantly when they graduate.
Matched MeSH terms: Medical Informatics/education; Medical Informatics/standards*
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.
E-health encompasses a wide scope and has excellent potential to grow in the future. Growing numbers of experts believe that e-health will fuel the next breakthroughs in health system improvements throughout the world. There is frequent evidence that largely indicates failures or unsustainable e-health implementations in different countries for different reasons. Iran is also a developing country that is presently applying this promising technology for its traditional healthcare delivery.
Matched MeSH terms: Medical Informatics Applications*
Public universities in Saudi Arabia today are making substantial investments in e-learning as part of their educational system, especially in the implementation of learning management systems (LMS). To our knowledge, this is the first study conducted in Saudi Arabia exploring medical students' experience with an LMS, particularly as part of a medical informatics course.
This paper provides a systematic review of safety use of health information technology (IT). The first objective is to identify the antecedents towards safety use of health IT by conducting systematic literature review (SLR). The second objective is to classify the identified antecedents based on the work system in Systems Engineering Initiative for Patient Safety (SEIPS) model and an extension of DeLone and McLean (D&M) information system (IS) success model.
This paper shall first investigate the informatics areas and applications of the four Traditional Medicine systems - Traditional Chinese Medicine (TCM), Ayurveda, Traditional Arabic and Islamic Medicine and Traditional Malay Medicine. Then, this paper shall examine the national informatics infrastructure initiatives in the four respective countries that support the Traditional Medicine systems. Challenges of implementing informatics in Traditional Medicine Systems shall also be discussed.
The urgent need for new classes of orally available, safe, and effective antivirals─covering a breadth of emerging viruses─is evidenced by the loss of life and economic challenges created by the HIV-1 and SARS-CoV-2 pandemics. As frontline interventions, small-molecule antivirals can be deployed prophylactically or postinfection to control the initial spread of outbreaks by reducing transmissibility and symptom severity. Natural products have an impressive track record of success as prototypic antivirals and continue to provide new drugs through synthesis, medicinal chemistry, and optimization decades after discovery. Here, we demonstrate an approach using computational analysis typically used for rational drug design to identify and develop natural product-inspired antivirals. This was done with the goal of identifying natural product prototypes to aid the effort of progressing toward safe, effective, and affordable broad-spectrum inhibitors of Betacoronavirus replication by targeting the highly conserved RNA 2'-O-methyltransferase (2'-O-MTase). Machaeriols RS-1 (7) and RS-2 (8) were identified using a previously outlined informatics approach to first screen for natural product prototypes, followed by in silico-guided synthesis. Both molecules are based on a rare natural product group. The machaeriols (3-6), isolated from the genus Machaerium, endemic to Amazonia, inhibited the SARS-CoV-2 2'-O-MTase more potently than the positive control, Sinefungin (2), and in silico modeling suggests distinct molecular interactions. This report highlights the potential of computationally driven screening to leverage natural product libraries and improve the efficiency of isolation or synthetic analog development.
Evaluating and selecting software packages that meet the requirements of an organization are difficult aspects of software engineering process. Selecting the wrong open-source EMR software package can be costly and may adversely affect business processes and functioning of the organization. This study aims to evaluate and select open-source EMR software packages based on multi-criteria decision-making. A hands-on study was performed and a set of open-source EMR software packages were implemented locally on separate virtual machines to examine the systems more closely. Several measures as evaluation basis were specified, and the systems were selected based a set of metric outcomes using Integrated Analytic Hierarchy Process (AHP) and TOPSIS. The experimental results showed that GNUmed and OpenEMR software can provide better basis on ranking score records than other open-source EMR software packages.
Poor information quality (IQ) must be understood as a business problem rather than systems problem. In health care organization, what is required is an effective quality management that continuously manages and reviews the factors influencing IQ in health information systems (HIS) so as to achieve the desired outcomes. Hence, in order to understand the issues of information quality management (IQM) practices in health care organizations, a more holistic evaluation study should be undertaken to investigate the IQM practices in health care organizations. It is the aim of this paper to identify the significant evaluation criteria that influence the production of good IQ in HIS.
Matched MeSH terms: Medical Informatics/standards*
Electronic patient records (EPR) can be regarded as an implicit source of clinical behaviour and problem-solving knowledge, systematically compiled by clinicians. We present an approach, together with its computational implementation, to pro-actively transform XML-based EPR into specialised Clinical Cases (CC) in the realm of Medical Case Base Systems. The 'correct' transformation of EPR to CC involves structural, terminological and conceptual standardisation, which is achieved by a confluence of techniques and resources, such as XML, UMLS (meta-thesaurus) and medical knowledge ontologies. We present below the functional architecture of a Medical Case-Base Reasoning Info-Structure (MCRIS) that features two distinct, yet related, functionalities: (1) a generic medical case-based reasoning system for decision-support activities; and (2) an EPR-CC transformation system to transform typical EPR's to CC.
Matched MeSH terms: Medical Informatics Computing*
Easier and focused access to healthcare information can empower individuals to make 'informed' choices and judgements about personal health maintenance. To achieve 'optimum' patient empowerment, we need to re-evaluate and potentially re-design the processes of healthcare information delivery. Our suggestion is that healthcare information should be personalised according to each individual's healthcare needs and it should be pro-actively delivered, i.e. pushed towards the individual. We present an intelligent Personalised Healthcare Information Delivery Systems that aims to enhance patient empowerment by pro-actively pushing customised, based on one's Electronic Medical Record, health maintenance information via the WWW.
Matched MeSH terms: Medical Informatics Computing*
Health-Level (HL) 7 message semantics allows effective functional implementation of Electronic Medical Record (EMR)--encompassing both clinical and administrative (i.e. demographic and financial) information--interchange systems, at the expense of complexity with respect the Protocol Data Unit (PDU) structure and the client-side application architecture. In this paper we feature the usage of the Extensible Markup Language (XML) document-object modelling and Java client-server connectivity towards the implementation of a Web-based system for EMR transaction processing. Our solution features an XML-based description of EMR templates, which are subsequently transcribed into a Hypertext Markup Language (HTML)-Javascript form. This allows client-side user interfaceability and server-side functionality--i.e. message validation, authentication and database connectivity--to be handled through standard Web client-server mechanisms, the primary assumption being availability of a browser capable of XML documents and the associated stylesheets. We assume usage of the Internet as the interchange medium, hence the necessity for authentication and data privacy mechanisms, both of which can be constructed using standard Java-based building blocks.
Matched MeSH terms: Medical Informatics Computing*
Since the first coronavirus disease 2019 (COVID-19) outbreak appeared in Wuhan, mainland China on December 31, 2019, the geographical spread of the epidemic was swift. Malaysia is one of the countries that were hit substantially by the outbreak, particularly in the second wave. This study aims to simulate the infectious trend and trajectory of COVID-19 to understand the severity of the disease and determine the approximate number of days required for the trend to decline. The number of confirmed positive infectious cases [as reported by Ministry of Health, Malaysia (MOH)] were used from January 25, 2020 to March 31, 2020. This study simulated the infectious count for the same duration to assess the predictive capability of the Susceptible-Infectious-Recovered (SIR) model. The same model was used to project the simulation trajectory of confirmed positive infectious cases for 80 days from the beginning of the outbreak and extended the trajectory for another 30 days to obtain an overall picture of the severity of the disease in Malaysia. The transmission rate, β also been utilized to predict the cumulative number of infectious individuals. Using the SIR model, the simulated infectious cases count obtained was not far from the actual count. The simulated trend was able to mimic the actual count and capture the actual spikes approximately. The infectious trajectory simulation for 80 days and the extended trajectory for 110 days depicts that the inclining trend has peaked and ended and will decline towards late April 2020. Furthermore, the predicted cumulative number of infectious individuals tallies with the preparations undertaken by the MOH. The simulation indicates the severity of COVID-19 disease in Malaysia, suggesting a peak of infectiousness in mid-March 2020 and a probable decline in late April 2020. Overall, the study findings indicate that outbreak control measures such as the Movement Control Order (MCO), social distancing and increased hygienic awareness is needed to control the transmission of the outbreak in Malaysia.
Matched MeSH terms: Public Health Informatics/methods*
Earlier evaluation studies on Health Information Systems (HIS) adoption have highlighted a large number of adoption problems that were attributed to the lack of fit between technology, human and organisation factors. Lessons can be learned from these evaluation studies by identifying the most important factors of HIS adoption. In order to study the adoption issue, a qualitative systematic review has been performed using a recently introduced framework, known as HOT-fit (Human, Organisation and Technology fit). The paper identifies and highlights the following critical adoption factors: technology (ease of use, system usefulness, system flexibility, time efficiency, information accessibility and relevancy); human (user training, user perception, user roles, user skills, clarity of system purpose, user involvement); organisation (leadership and support, clinical process, user involvement, internal communication, inter organisational system, as well as the fit between them. The findings can be used to guide future system development and inform relevant decision making.
Healthy farming systems play a vital role in improving agricultural productivity and sustainable food production. The present study aimed to propose an efficient framework to evaluate ecologically viable and economically sound farming systems using a matrix-based analytic hierarchy process (AHP) and weighted linear combination method with geo-informatics tools. The proposed framework has been developed and tested in the Central Highlands of Sri Lanka. Results reveal that more than 50% of farming systems demonstrated moderate status in terms of ecological and economic aspects. However, two vulnerable farming systems on the western slopes of the Central Highlands, named WL1a and WM1a, were identified as very poor status. These farming systems should be a top priority for restoration planning and soil conservation to prevent further deterioration. Findings indicate that a combination of ecologically viable (nine indicators) and economical sound (four indicators) criteria are a practical method to scrutinize farming systems and decision making on soil conservation and sustainable land management. In addition, this research introduces a novel approach to delineate the farming systems based on agro-ecological regions and cropping areas using geo-informatics technology. This framework and methodology can be employed to evaluate the farming systems of other parts of the country and elsewhere to identify ecologically viable and economically sound farming systems concerning soil erosion hazards. The proposed approach addresses a new dimension of the decision-making process by evaluating the farming systems relating to soil erosion hazards and suggests introducing policies on priority-based planning for conservation with low-cost strategies for sustainable land management.
In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable lighting condition and naked eye's ability to capture the exact colour distribution on the tongue especially the tongue with multicolour substance. To overcome this ambiguity, this paper presents a two-stage tongue's multicolour classification based on a support vector machine (SVM) whose support vectors are reduced by our proposed k-means clustering identifiers and red colour range for precise tongue colour diagnosis. In the first stage, k-means clustering is used to cluster a tongue image into four clusters of image background (black), deep red region, red/light red region, and transitional region. In the second-stage classification, red/light red tongue images are further classified into red tongue or light red tongue based on the red colour range derived in our work. Overall, true rate classification accuracy of the proposed two-stage classification to diagnose red, light red, and deep red tongue colours is 94%. The number of support vectors in SVM is improved by 41.2%, and the execution time for one image is recorded as 48 seconds.
Matched MeSH terms: Medical Informatics/instrumentation; Medical Informatics/methods*