177 research outputs found
Missed opportunities in health care education evidence synthesis
We read with excitement the systematic review on how to teach evidence-based medicine (EBM) to medical trainees.1 The conclusions of the paper1 represent a concise and accurate reļ¬ection of this large synthesis of evidence. Unfortunately, we were left reļ¬ecting not on the evidence base illuminated by this review, but on the missed opportunities we will highlight herein. These examples are not in any way meant to represent a speciļ¬c set of criticisms of this work,1 but, rather, are intended as exemplars of wider methodological issues that currently exist within much published material on the synthesis of evidence in health care educatio
Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms
Horizontal well placement determination within a reservoir is a significant and difficult
step in the reservoir development process. Determining the optimal well location is a
complex problem involving many factors including geological considerations, reservoir
and fluid properties, economic costs, lateral direction, and technical ability. The most
thorough approach to this problem is that of an exhaustive search, in which a simulation
is run for every conceivable well position in the reservoir. Although thorough and
accurate, this approach is typically not used in real world applications due to the time
constraints from the excessive number of simulations.
This project suggests the use of a genetic algorithm applied to the horizontal well
placement problem in a gas reservoir to reduce the required number of simulations. This
research aims to first determine if well placement optimization is even necessary in a gas
reservoir, and if so, to determine the benefit of optimization. Performance of the genetic
algorithm was analyzed through five different case scenarios, one involving a vertical well and four involving horizontal wells. The genetic algorithm approach is used to
evaluate the effect of well placement in heterogeneous and anisotropic reservoirs on
reservoir recovery. The wells are constrained by surface gas rate and bottom-hole
pressure for each case.
This project's main new contribution is its application of using genetic algorithms to
study the effect of well placement optimization in gas reservoirs. Two fundamental
questions have been answered in this research. First, does well placement in a gas
reservoir affect the reservoir performance? If so, what is an efficient method to find the
optimal well location based on reservoir performance? The research provides evidence
that well placement optimization is an important criterion during the reservoir
development phase of a horizontal-well project in gas reservoirs, but it is less significant
to vertical wells in a homogeneous reservoir. It is also shown that genetic algorithms are
an extremely efficient and robust tool to find the optimal location
Educating for planetary health and environmentally sustainable health care: Responding with urgency
How to review a paper on medical education
There has been a substantial increase in the number of medical and health professional education manuscripts being submitted to an increasing number of journals in this field.Ā More reviews and more reviewers are needed to facilitate discussion of both relevance and quality of those manuscripts.Ā MedEdPublish relies on readers and Review Panel members to contribute to this process, thereby helping to maintain standards in medical and health professional education publishing.Ā This article provides guidance that is most relevant to reviewers and potential authorsĀ for MedEdPublish, but may be relevant to publishing in other medical and health professional journals
AMEE guide 94: Systematic reviews in medical education: A practical approach
The twentieth century saw a paradigm shift in medical education, with acceptance that āknowledgeā and ātruthā are contextual, in flux and always evolving. The twenty-first century has seen a greater explosion in computer technology leading to a massive increase in information and an ease of availability, both offering great potential to future research. However, for many decades, there have been voices within the health care system raising an alarm at the lack of evidence to support widespread clinical practice; from these voices, the concept of and need for evidence-based health-care has grown. Parallel to this development has been the emergence of evidence-based medical education; if healthcare is evidence-based, then the training of practitioners who provide this healthcare must equally be evidence-based. Evidence-based medical education involves the systematic collection, synthesis and application of all available evidence, when available, and not just the opinion of experts. This represented a seismic shift from a position of expert based consensus guidance to evidence led guidance for evolving clinical knowledge. The aim of this guide is to provide a practical approach to the development and application of a systematic review in medical education; a valid method used in this guide to seek and substantiate the effects of interventions in medical education
Health Professions' Educators' Adaptation to Rapidly Changing Circumstances: The Ottawa 2020 Conference Experience
Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms
Horizontal well placement determination within a reservoir is a significant and difficult
step in the reservoir development process. Determining the optimal well location is a
complex problem involving many factors including geological considerations, reservoir
and fluid properties, economic costs, lateral direction, and technical ability. The most
thorough approach to this problem is that of an exhaustive search, in which a simulation
is run for every conceivable well position in the reservoir. Although thorough and
accurate, this approach is typically not used in real world applications due to the time
constraints from the excessive number of simulations.
This project suggests the use of a genetic algorithm applied to the horizontal well
placement problem in a gas reservoir to reduce the required number of simulations. This
research aims to first determine if well placement optimization is even necessary in a gas
reservoir, and if so, to determine the benefit of optimization. Performance of the genetic
algorithm was analyzed through five different case scenarios, one involving a vertical well and four involving horizontal wells. The genetic algorithm approach is used to
evaluate the effect of well placement in heterogeneous and anisotropic reservoirs on
reservoir recovery. The wells are constrained by surface gas rate and bottom-hole
pressure for each case.
This project's main new contribution is its application of using genetic algorithms to
study the effect of well placement optimization in gas reservoirs. Two fundamental
questions have been answered in this research. First, does well placement in a gas
reservoir affect the reservoir performance? If so, what is an efficient method to find the
optimal well location based on reservoir performance? The research provides evidence
that well placement optimization is an important criterion during the reservoir
development phase of a horizontal-well project in gas reservoirs, but it is less significant
to vertical wells in a homogeneous reservoir. It is also shown that genetic algorithms are
an extremely efficient and robust tool to find the optimal location
Impact of the COVID-19 pandemic: The perceptions of health professions educators
What are health professions educators doing during the COVID-19 pandemic? A search of articles in MedEdPublish on the topics of COVID-19 revealed 39 articles published in the first 3 months of the pandemic. Topics included curriculum adaptation, guidelines for using technology, assessment adaptation, impact on students, faculty and career development, and conference adaptation. There was significant overlap among articles, particularly those discussing teaching, learning, and assessment practices. Common themes were adaptation, innovation, remote delivery, flexibility in the face of a pandemic, and how to continue to educate and graduate competent health professionals. All articles were descriptive, and none included data describing efficacy, likely due to the short timeline since the pandemicās inception. Additional study is necessary to produce evidence for the teaching and assessment adaptations described. Some changes are likely to persist longer-term and may outlast the pandemic itself
Oculomotor atypicalities in motor neurone disease: a systematic review
Introduction: Cognitive dysfunction is commonplace in Motor Neurone Disease (MND). However, due to the prominent motor symptoms in MND, assessing patientsā cognitive function through traditional cognitive assessments, which oftentimes require motoric responses, may become increasingly challenging as the disease progresses. Oculomotor pathways are apparently resistant to pathological degeneration in MND. As such, abnormalities in oculomotor functions, largely driven by cognitive processes such as saccades and smooth pursuit eye movement, may be reflective of frontotemporal cognitive deficits in MND. Thus, saccadic and smooth pursuit eye movements may prove to be ideal mechanistic markers of cognitive function in MND. Methods: To ascertain the utility of saccadic and smooth pursuit eye movements as markers of cognitive function in MND, this review summarizes the literature concerning saccadic and smooth pursuit eye movement task performance in people with MND. Results and discussion: Of the 22 studies identified, noticeable patterns suggest that people with MND can be differentiated from controls based on antisaccade and smooth pursuit task performance, and thus the antisaccade task and smooth pursuit task may be potential candidates for markers of cognition in MND. However, further studies which ascertain the concordance between eye tracking measures and traditional measures of cognition are required before this assumption is extrapolated, and clinical recommendations are made. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=376620, identifier CRD42023376620
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