The final examination in medicine : time for change?

Most medical programmes culminate in a final assessment, in order that participants may be tested and graded. In June 1995, at the University of Malta, a group of 53 medical students sat for their final examination; medicine was one of the three co-equal component subjects of this statutory qualifying examination. The scope of this paper is to analyze the results obtained in the final examination in medicine and to use this data to address such issues as aims of this examination, method and quality assurance of assessment. The result obtained by candidates in the final examination in medicine was correlated with their university entry qualifications. The composite mark for each candidate was split into its components and analysis took the form of description, correlation and clustering. Computation of Cronbach’s alpha facilitated anlaysis of reliability of each of the three parts of the examination. The findings of this paper suggest that there is room for improving the quality of assessment methods. A review of methods and procedures, with the dual purpose of decreasing bias and increasing specificity and sensitivity of this statutory examination will not only benefit candidates, but ultimately also the University of Malta. The final qualifying examination in medicine should have clearly defined objectives and methods of assessment should be aimed specifically at reaching them. It needs to be able to assess the ability to think critically about diagnosis and management and to ensure that the candidate has a satisfactory base of factual knowledge. It also needs to assess objectively the adequacy of basic clinical skills and candidates’ facility of communication.peer-reviewe

Medical imaging analysis with artificial neural networks

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging

Chronic Exposure to Triclosan Sustains Microbial Community Shifts and Alters Antibiotic Resistance Gene Levels in Anaerobic Digesters

Triclosan, an antimicrobial chemical found in consumer personal care products, has been shown to stimulate antibiotic resistance in pathogenic bacteria. Although many studies focus on antibiotic resistance pertinent to medical scenarios, resistance developed in natural and engineered environments is less studied and has become an emerging concern for human health. In this study, the impacts of chronic triclosan (TCS) exposure on antibiotic resistance genes (ARGs) and microbial community structure were assessed in lab-scale anaerobic digesters. TCS concentrations from below detection to 2500 mg kg−1 dry solids were amended into anaerobic digesters over 110 days and acclimated for \u3e3 solid retention time values. Four steady state TCS concentrations were chosen (30–2500 mg kg−1). Relative abundance of mexB, a gene coding for a component of a multidrug efflux pump, was significantly higher in all TCS-amended digesters (30 mg kg−1 or higher) relative to the control. TCS selected for bacteria carrying tet(L) and against those carrying erm(F) at concentrations which inhibited digester function; the pH decrease associated with digester failure was suspected to cause this selection. Little to no impact of TCS was observed on intI1 relative abundance. Microbial communities were also surveyed by high-throughput 16S rRNA gene sequencing. Compared to the control digesters, significant shifts in community structure towards clades containing commensal and pathogenic bacteria were observed in digesters containing TCS. Based on these results, TCS should be included in studies and risk assessments that attempt to elucidate relationships between chemical stressors (e.g. antibiotics), antibiotic resistance genes, and public health

Multilevel Weighted Support Vector Machine for Classification on Healthcare Data with Missing Values

This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Such data is invariably problematic: noisy, with missing entries, with imbalance in classes of interests, leading to serious bias in predictive modeling. Since standard data mining methods often produce poor performance measures, we argue for development of specialized techniques of data-preprocessing and classification. In this paper, we propose a new method to simultaneously classify large datasets and reduce the effects of missing values. It is based on a multilevel framework of the cost-sensitive SVM and the expected maximization imputation method for missing values, which relies on iterated regression analyses. We compare classification results of multilevel SVM-based algorithms on public benchmark datasets with imbalanced classes and missing values as well as real data in health applications, and show that our multilevel SVM-based method produces fast, and more accurate and robust classification results.Comment: arXiv admin note: substantial text overlap with arXiv:1503.0625

Triclocarban Influences Antibiotic Resistance and Alters Anaerobic Digester Microbial Community Structure

Triclocarban (TCC) is one of the most abundant organic micropollutants detected in biosolids. Lab-scale anaerobic digesters were amended with TCC at concentrations ranging from the background concentration of seed biosolids (30 mg/kg) to toxic concentrations of 850 mg/kg to determine the effect on methane production, relative abundance of antibiotic resistance genes, and microbial community structure. Additionally, the TCC addition rate was varied to determine the impacts of acclimation time. At environmentally relevant TCC concentrations (max detect = 440 mg/kg), digesters maintained function. Digesters receiving 450 mg/kg of TCC maintained function under gradual TCC addition, but volatile fatty acid concentrations increased, pH decreased, and methane production ceased when immediately fed this concentration. The concentrations of the mexB gene (encoding for a multidrug efflux pump) were higher with all concentrations of TCC compared to a control, but higher TCC concentrations did not correlate with increased mexB abundance. The relative abundance of the gene tet(L) was greater in the digesters that no longer produced methane, and no effect on the relative abundance of the class 1 integron integrase encoding gene (intI1) was observed. Illumina sequencing revealed substantial community shifts in digesters that functionally failed from increased levels of TCC. More subtle, yet significant, community shifts were observed in digesters amended with TCC levels that did not inhibit function. This research demonstrates that TCC can select for a multidrug resistance encoding gene in mixed community anaerobic environments, and this selection occurs at concentrations (30 mg/kg) that can be found in full-scale anaerobic digesters (U.S. median concentration = 22 mg/kg, mean = 39 mg/kg)

Chronic non-specific low back pain - sub-groups or a single mechanism?

Copyright 2008 Wand and O'Connell; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Low back pain is a substantial health problem and has subsequently attracted a considerable amount of research. Clinical trials evaluating the efficacy of a variety of interventions for chronic non-specific low back pain indicate limited effectiveness for most commonly applied interventions and approaches. Discussion: Many clinicians challenge the results of clinical trials as they feel that this lack of effectiveness is at odds with their clinical experience of managing patients with back pain. A common explanation for this discrepancy is the perceived heterogeneity of patients with chronic non-specific low back pain. It is felt that the effects of treatment may be diluted by the application of a single intervention to a complex, heterogeneous group with diverse treatment needs. This argument presupposes that current treatment is effective when applied to the correct patient. An alternative perspective is that the clinical trials are correct and current treatments have limited efficacy. Preoccupation with sub-grouping may stifle engagement with this view and it is important that the sub-grouping paradigm is closely examined. This paper argues that there are numerous problems with the sub-grouping approach and that it may not be an important reason for the disappointing results of clinical trials. We propose instead that current treatment may be ineffective because it has been misdirected. Recent evidence that demonstrates changes within the brain in chronic low back pain sufferers raises the possibility that persistent back pain may be a problem of cortical reorganisation and degeneration. This perspective offers interesting insights into the chronic low back pain experience and suggests alternative models of intervention. Summary: The disappointing results of clinical research are commonly explained by the failure of researchers to adequately attend to sub-grouping of the chronic non-specific low back pain population. Alternatively, current approaches may be ineffective and clinicians and researchers may need to radically rethink the nature of the problem and how it should best be managed