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Early detection of causal relationships between drugs and their associated adverse drug reactions (ADRs) can prevent harmful consequences or even deaths. Rare ADRs cannot be detected by pre-marketing clinical trials due to limitations in their size and duration. Existing postmarketing surveillance methods mainly rely on spontaneous reporting which is limited by severe underreporting (<;10 percentage...
Each HIV-1 patient has a diverse population of virus strains in his/her body as the virus quickly replicates and mutates, requiring a combination drug therapy optimized to the patient's unique viral population. Towards this goal, prediction systems have been developed to deduce the susceptibility of a given HIV genotype to a single drug. Many are rule-based systems or rely on hand-crafted features...
Herbal Medicine in Traditional Chinese Medicine (TCM) relies on interactions between ingredients of a prescription. The combination is chosen to promote desirable interactions. Analysing these interactions is important in quantitatively analysing effects of TCM on patient outcomes. The concept of interactions has not been adequately formulated before due to the ambiguity of “interaction” and the need...
In this paper, we analyse the behaviour of osteosarcoma cancer cells which are either exposed to the anticancer agent Topotecan or not exposed to any external agent. For the analyses of cell lineage data encoded from time lapse microscopy, we choose data mining tools that generate interpretable models of the data, and we address their statistical significance. We consider the mortality of unexposed...
This paper presents a computational approach to HIV Drug discovery using rough set based rule induction. Since conventional drug discovery is a time consuming process in which drugs are discovered either by chance or by screening the natural products, alternative methods were required to hasten the process in order to abridge the demand and supply gap. Chemoinformatics, providing novel methodologies...
The work is motivated by real-world applications of detecting Adverse Drug Reactions (ADRs) from administrative health databases. ADRs are a leading cause of hospitalization and death worldwide. Almost all current postmarket ADR signaling techniques are based on spontaneous ADR case reports, which suffer from serious underreporting and latency. However, administrative health data are widely and routinely...
In this paper, a new algorithm related with feature selection method mostly used in data mining, machine learning and pattern recognition areas is proposed. Classical Fukunaga-Koontz Transform is extended to a binary kernel classifier. We used cDNA microarrays to assess 11.000 gene expression profiles in 60 human cancer cell lines used in a drug discovery screen by the National Cancer Institute and...
Many advances in medicine, but the occurrence of errors that accompany the completion of forms are inevitable for the human condition [3]. An information system is to achieve the prescription indicating possible drug interactions, reducing a large number of incidents related to medical errors. The implementation of the system also reduces the time of hospital beds and administrative costs, allowing...
Mutant protein hSKCa3 responsible for Schizophrenia is taken from NCBI's Entrez database; its 3D structure is determined by homology modelling. The conotoxin protein is taken from NCBI's Entrez database & its 3D structure is established. The structure of Withanolide is determined and docked with conotoxin protein; this combination is docked with hSKCa3 protein, hence establishing a remedy.
The objective of this study was to develop neural network model of drug release from HPMC matrix tablets in terms of formulation factors and process variables. The physicochemical properties of the drug and HPMC and manufacturing process were investigated and used as independent factors. The % cumulative release of different drugs from hyroxypropylmethylcellulose (HPMC) matrix tablets was used as...
The combined analysis of the microarray and drug-activity datasets has the potential of revealing valuable knowledge about various relations among gene expressions and drug activity patterns in tumor cells. However, the huge amount of biological data needs appropriate data mining models in order to extract interesting patterns and useful information. In this paper, the NCI60 dataset has been analyzed...
Diabetes is a common disease, and one in which the patient has to undergo many lifestyle changes. In this paper we propose a model in which fuzzy logic can be used to determine the amount of insulin to be dosed to a diabetic, without the person having to calculate the same every half hour. Such systems have already been proposed, and we have worked based on already existing papers. This system uses...
Oral anticoagulation therapy, largely performed by warfarin-based drugs, is commonly used for patients with a high risk of blood clotting which can lead to stroke or thrombosis. The state of the patient, with respect to anticoagulation, is captured by the index INR, which is to be kept within a therapeutic range. The patients' response is marked by high interindividual and inter-temporal variability,...
As basic science (ldquobenchrdquo) and medical practice (ldquobedsiderdquo) continue their exponential growth in complexity and scope, the need for finding hidden connections and translating knowledge across disciplines becomes inevitable. The proposed method combines semantic Web technology, graph algorithms, and user profiling to discover and prioritize novel cross-disciplinary associations based...
Designing appropriate graphs is a problem frequently occurring in several common applications ranging from designing communication and transportation networks to discovering new drugs. More often than not the graphs to be designed need to satisfy multiple, sometimes conflicting, objectives e.g. total length, cost, complexity or other shape and property limitations. In this paper we present our approach...
With the arrival of an aging society, and the average period of ill for the old is much longer than the period of health, at the same time, there are various drugs and difficult dosage for the old, while there are adverse information recognition on drug packaging, coupled with the old special physiological and psychological characteristics, all of which must make the old forget or make a mistake in...
Adverse Drug Events (ADEs) are currently considered as a major public health issue, resulting in endangering patients' safety and significant healthcare costs. The EU-funded project PSIP (Patient Safety through Intelligent Procedures in Medication) aims to develop intelligent mechanisms towards preventing ADEs, aiming to improve the entire Prescription - Dispensation - Administration - Compliance...
In March and April 2009, an outbreak of H1N1 influenza in Mexico led to hundreds of confirmed cases and a number of deaths. The worldwide spread of H1N1 had attracted everyone's attention and arisen an overwhelm fear. Up to now, there is still an urgent need in the solution for ending this light. In this study, a QSAR model of neuraminidase (NA) type 1 (N1) provides an access. The pharmacophore map...
One of the main tasks of KDTCM (knowledge discovery in traditional Chinese medicine) is discovering novel paired or grouped drugs from Chinese medical formula database. Paired or grouped drugs, which are special combinations of two or more drugs, have strong efficacy. Association rule mining is used by reason of the large number of association relationships among various kinds of drugs. However, association...
Counterfeit pharmaceutical products pose a serious public health problem. It is thus important not only to detect them, but also to identify their composition and assess the risk for the patient. Identifying the spectral signatures of the pure compounds present in a (maybe counterfeit) tablet of unknown origin is clearly a hyperspectral unmixing problem. In fact, under a linear mixing model, the hyperspectral...
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