946 resultados para medical imaging
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Perhaps no other patient safety intervention depends so acutely on effective interprofessional teamwork for patient survival than the hospital rapid response system (RRS). Yet little is known about nurse-physician relationships when rescuing at-risk patients. This study compared nursing and medical staff perceptions of a mature RRS at a large tertiary hospital. Findings indicate the RRS may be failing to address a hierarchical culture and systems-level barriers to early recognition and response to patient deterioration.
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Background The use of Electronic Medical Record (EMR) systems is increasing internationally, though developing countries, such as Saudi Arabia, have tended to lag behind in the adoption and implementation of EMR systems due to several barriers. The literature shows that the main barriers to EMR in Saudi Arabia are lack of knowledge or experience using EMR systems and staff resistance to using the implemented EMR system. Methods A quantitative methodology was used to examine health personnel knowledge and acceptance of and preference for EMR systems in seven Saudi public hospitals in Jeddah, Makkah and Taif cities. Results Both English literacy and education levels were significantly correlated with computer literacy and EMR literacy. Participants whose first language was not Arabic were more likely to prefer using an EMR system compared to those whose first language was Arabic. Conclusion This study suggests that as computer literacy levels increase, so too do staff preferences for using EMR systems. Thus, it would be beneficial for hospitals to assess English language proficiency and computer literacy levels of staff prior to implementing an EMR system. It is recommended that hospitals need to offer training and targeted educational programs to the potential users of the EMR system. This would help to increase English language proficiency and computer literacy levels of staff as well as staff acceptance of the system.
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Background As the increasing adoption of information technology continues to offer better distant medical services, the distribution of, and remote access to digital medical images over public networks continues to grow significantly. Such use of medical images raises serious concerns for their continuous security protection, which digital watermarking has shown great potential to address. Methods We present a content-independent embedding scheme for medical image watermarking. We observe that the perceptual content of medical images varies widely with their modalities. Recent medical image watermarking schemes are image-content dependent and thus they may suffer from inconsistent embedding capacity and visual artefacts. To attain the image content-independent embedding property, we generalise RONI (region of non-interest, to the medical professionals) selection process and use it for embedding by utilising RONI’s least significant bit-planes. The proposed scheme thus avoids the need for RONI segmentation that incurs capacity and computational overheads. Results Our experimental results demonstrate that the proposed embedding scheme performs consistently over a dataset of 370 medical images including their 7 different modalities. Experimental results also verify how the state-of-the-art reversible schemes can have an inconsistent performance for different modalities of medical images. Our scheme has MSSIM (Mean Structural SIMilarity) larger than 0.999 with a deterministically adaptable embedding capacity. Conclusions Our proposed image-content independent embedding scheme is modality-wise consistent, and maintains a good image quality of RONI while keeping all other pixels in the image untouched. Thus, with an appropriate watermarking framework (i.e., with the considerations of watermark generation, embedding and detection functions), our proposed scheme can be viable for the multi-modality medical image applications and distant medical services such as teleradiology and eHealth.
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To report the outcomes of a randomised educational trial of a new methodology for extended immersion in medical simulation for senior medical students. Clinical Learning through Extended Immersion in Medical Simulation (CLEIMS) is a new methodology for medical student learning. It involves senior students working in teams of 4-5 through the clinical progress of one or more patients over a week, utilising a range of simulation methodologies (simulated patient assessment, simulated significant other briefing, virtual story continuations, pig-trotter wound repair, online simulated on-call modules, interprofessional simulated ward rounds and high fidelity mannequin-based emergency simulations), to enhance learning in associated workshops and seminars. A randomised educational trial comparing the methodology to seminars and workshops alone began in 2010 and interim results were reported at last year’s conference. Updated results are presented here and final primary endpoint outcomes will be available by the time of the conference.
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This structural magnetic resonance imaging study examined the relationship between pituitary gland volume (PGV) and lifetime number of parasuicidal behaviors in a first-presentation, teenage borderline personality disorder (BPD) sample with minimal exposure to treatment. Hierarchical regression analysis revealed that age and number of parasuicidal behaviors were significant predictors of PGV. These findings indicate that parasuicidal behavior in BPD might be associated with greater activation of the hypothalamic-pituitary-adrenal (HPA) axis. Further studies are required using direct neuroendocrine measures and exploring other parameters of self-injurious behavior, such as recency of self-injurious behavior, intent to die and medical threat.
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Asoftware-based environment was developed to provide practical training in medical radiation principles and safety. The Virtual Radiation Laboratory application allowed students to conduct virtual experiments using simulated diagnostic and radiotherapy X-ray generators. The experiments were designed to teach students about the inverse square law, half value layer and radiation protection measures and utilised genuine clinical and experimental data. Evaluation of the application was conducted in order to ascertain the impact of the software on students’ understanding, satisfaction and collaborative learning skills and also to determine potential further improvements to the software and guidelines for its continued use. Feedback was gathered via an anonymous online survey consisting of a mixture of Likert-style questions and short answer open questions. Student feedback was highly positive with 80 % of students reporting increased understanding of radiation protection principles. Furthermore 72 % enjoyed using the software and 87 %of students felt that the project facilitated collaboration within small groups. The main themes arising in the qualitative feedback comments related to efficiency and effectiveness of teaching, safety of environment, collaboration and realism. Staff and students both report gains in efficiency and effectiveness associated with the virtual experiments. In addition students particularly value the visualisation of ‘‘invisible’’ physical principles and increased opportunity for experimentation and collaborative problembased learning. Similar ventures will benefit from adopting an approach that allows for individual experimentation while visualizing challenging concepts.
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"Using the nursing process as a framework for practice, the fourth edition has been extensively revised to reflect the rapid changing nature of nursing practice and the increasing focus on key nursing care priorities. Building on the strengths of the third Australian and New Zealand edition and incorporating relevant global nursing research and practice from the prominent US title Medical-Surgical Nursing, 9Th Edition, Lewis’s Medical-Surgical Nursing, 4th Edition is an essential resource for students seeking to understand the role of the professional nurse in the contemporary health environment."--Publisher website
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BACKGROUND Law is increasingly involved in clinical practice, particularly at the end of life, but undergraduate and postgraduate education in this area remains unsystematic. We hypothesised that attitudes to and knowledge of the law governing withholding/withdrawing treatment from adults without capacity (the WWLST law) would vary and demonstrate deficiencies among medical specialists. AIMS We investigated perspectives, knowledge and training of medical specialists in the three largest (populations and medical workforces) Australian states, concerning the WWLST law. METHODS Following expert legal review, specialist focus groups, pre-testing and piloting in each state, seven specialties involved with end-of-life care were surveyed, with a variety of statistical analyses applied to the responses. RESULTS Respondents supported the need to know and follow the law. There were mixed views about its helpfulness in medical decision-making. Over half the respondents conceded poor knowledge of the law; this was mirrored by critical gaps in knowledge that varied by specialty. There were relatively low but increasing rates of education from the undergraduate to continuing professional development (CPD) stages. Mean knowledge score did not vary significantly according to undergraduate or immediate postgraduate training, but CPD training, particularly if recent, resulted in greater knowledge. Case-based workshops were the preferred CPD instruction method. CONCLUSIONS Teaching of current and evolving law should be strengthened across all stages of medical education. This should improve understanding of the role of law, ameliorate ambivalence towards the law, and contribute to more informed deliberation about end-of-life issues with patients and families.
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This project was the first national study of the health and wellbeing of medical students in Vietnam. Data from over 2,000 students from eight universities indicate that, while the majority are healthy, significant proportions have poor mental and/or physical health and other life adversities. For many students, heavy academic demands were not a major stressor; rather, difficulties within their family, interpersonal relations, dissatisfaction with career choice and housing and financial problems appear to cause the most strain. This study provides evidence that will be useful for the development of professional counseling services in Vietnamese universities.
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Predictors of people’s intention to register with a body bequest program for donating their deceased body to medical science and research were examined using standard theory of planned behavior (TPB) predictors (attitude, subjective norm, perceived behavioral control) and adding moral norm, altruism, and knowledge. Australian students (N = 221) at a university with a recently established body bequest program completed measures of the TPB’s underlying beliefs (behavioral, normative, and control beliefs) and standard and extended TPB predictors, with a sub-sample reporting their registration-related behavior 2 months later. The standard TPB accounted for 43.6%, and the extended predictors an additional 15.1% of variance in intention. The significant predictors were attitude, subjective norm, and moral norm, partially supporting an extended TPB in understanding people’s body donation intentions. Further, important underlying beliefs can inform strategies to target prospective donors.
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In medical negligence litigation expert evidence has long played a dominant role. The trend towards the use of concurrent expert evidence is now well underway. However, for the lawyers and the doctors involved, the pathway is not yet familiar. Disputes have frequently arisen in the context of pre-hearing expert conclaves, given the adversarial nature of litigation and perhaps fuelled by fears of a less transparent process at this increasingly important stage. This article explains the concurrent expert evidence framework and examines areas of common dispute both in the conclaves and at trial, with a view to providing assistance to legal practitioners working in this area and the medical practitioners called upon to provide expert evidence in such litigation.
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Objective This paper presents an automatic active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort, and (2) the robustness of incremental active learning framework across different selection criteria and datasets is determined. Materials and methods The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional Random Fields as the supervised method, and least confidence and information density as two selection criteria for active learning framework were used. The effect of incremental learning vs. standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. Two clinical datasets were used for evaluation: the i2b2/VA 2010 NLP challenge and the ShARe/CLEF 2013 eHealth Evaluation Lab. Results The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared to the Random sampling baseline, the saving is at least doubled. Discussion Incremental active learning guarantees robustness across all selection criteria and datasets. The reduction of annotation effort is always above random sampling and longest sequence baselines. Conclusion Incremental active learning is a promising approach for building effective and robust medical concept extraction models, while significantly reducing the burden of manual annotation.
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Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all metaanalyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.
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We report the first 3D maps of genetic effects on brain fiber complexity. We analyzed HARDI brain imaging data from 90 young adult twins using an information-theoretic measure, the Jensen-Shannon divergence (JSD), to gauge the regional complexity of the white matter fiber orientation distribution functions (ODF). HARDI data were fluidly registered using Karcher means and ODF square-roots for interpol ation; each subject's JSD map was computed from the spatial coherence of the ODFs in each voxel's neighborhood. We evaluated the genetic influences on generalized fiber anisotropy (GFA) and complexity (JSD) using structural equation models (SEM). At each voxel, genetic and environmental components of data variation were estimated, and their goodness of fit tested by permutation. Color-coded maps revealed that the optimal models varied for different brain regions. Fiber complexity was predominantly under genetic control, and was higher in more highly anisotropic regions. These methods show promise for discovering factors affecting fiber connectivity in the brain.