Minimum dataset for head and neck cancer.
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Cancer Care Facilities↗
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An interface for precise and comfortable 3D work with volumetric medical datasets.
We have developed a 3D/2D paradigm of interaction that combines manipulation of precise 3D volumetric data with unambiguous widget interaction. Precise 3D interaction is ensured by a combination of resting the lower arms on an armrest and pivoting the hands around the wrist. Unambiguous 2D interaction is achieved by providing passive haptic feedback by means of a virtual control panel whose position coincides with the physical surfaces encasing the system. We have tested this interface with a neurosurgical planning application that has been clinically used for 17 skull-base cases at two local hospitals.
Computer Simulation↗
A dataset generator for whole genome shotgun sequencing.
Simulated data sets have been found to be useful in developing software systems because (1) they allow one to study the effect of a particular phenomenon in isolation, and (2) one has complete information about the true solution against which to measure the results of the software. In developing a software suite for assembling a whole human genome shotgun data set, we have developed a simulator, celsim, that permits one to describe and stochastically generate a target DNA sequence with a variety of repeat structures, to further generate polymorphic variants if desired, and to generate a shotgun data set that might be sampled from the target sequence(s). We have found the tool invaluable and quite powerful, yet the design is extremely simple, employing a special type of stochastic grammar.
Base Sequence↗
Interobserver agreement among sleep scorers from different centers in a large dataset.
STUDY OBJECTIVES: To evaluate epoch by epoch agreement in sleep stage assignment between scorers from different laboratories. DESIGN: N/A. METHODS: 62 NPSGs were selected for analysis from 3 sleep centers (38 diagnostic studies for sleep disordered breathing [SDB], 10 studies during CPAP titration, and 14 studies in subjects with no sleep related complaints or sleep pathology). The sleep recording montage consisted of at least 2 EEG leads, left and right EOG and a submental EMG. Scoring was performed manually by 5 experienced sleep technologists. No scorer had knowledge of any other scorers' results. Agreement was tabulated both for sleep stage distribution and on an epoch by epoch basis for the entire data set and the normal and SDB subsets. MEASUREMENTS AND RESULTS: The mean epoch by epoch agreement between scorers for all records was 73% (range 67-82%). Agreements were higher in the normal subset (mean 76%, range 65-85%) than in the SDB subset (mean 71%, range 65-78%). There was significant variability in agreement between records and between pairs of scorers. Overall, 75% of epochs had at least 4 of the 5 scorers in agreement on the sleep stage and 96% of epochs had agreement of at least 3 of the 5 scorers. CONCLUSIONS: The level of agreement in sleep stage assignment varies between scorers, by diagnosis, and by record. The level of agreement between laboratories is lower than what can be maintained between scorers within the same laboratory. This warrants caution when comparing data scored in separate laboratories. The lower agreement in SDB patients supports the generally held view that sleep fragmentation makes application of the R&K rules less reliable.
Adolescent↗
Discriminant histological features in the diagnosis of chronic idiopathic inflammatory bowel disease: analysis of a large dataset by a novel data visualisation technique.
BACKGROUND/AIMS: The histopathological assessment of endoscopic colorectal biopsies is important in the distinction between normality and chronic idiopathic inflammatory bowel disease, and between ulcerative colitis and Crohn's disease, in subjects with symptoms of bowel dysfunction. This study aims to use carefully defined histopathological observations on a large study population to produce systems that improve classification into these diagnostic categories. METHODS: Eight hundred and nine endoscopic colorectal biopsies with verified outcomes (165 normal, 473 ulcerative colitis, 171 Crohn's disease) were examined by a single experienced histopathologist and 20 defined features were recorded for each case using a novel graphical interface with reference images of each feature. These features, together with age and sex, were used to produce and test statistical classifiers using logistic regression and a novel growing cell structure technique. RESULTS: The distinction between chronic idiopathic inflammatory bowel disease and normality was made with a good level of performance by both statistical classifiers (with areas under the receiver operating characteristic curves above 0.80). The growing cell structure system selected features as discriminant that agreed with the published literature. Logistic regression produced a more variable selection of discriminant features because of the high correlation between many features. The distinction between ulcerative colitis and Crohn's disease was performed less accurately, with areas under the receiver operating characteristic curves of about 0.70. Again the features selected as discriminant broadly agreed with those in the published literature. CONCLUSIONS: Histopathological examination of endoscopic colorectal biopsies is an effective method of distinguishing between subjects with chronic idiopathic inflammatory bowel disease and normality, but less good at distinguishing between ulcerative colitis and Crohn's disease. The features selected as discriminant in this large statistical analysis broadly agree with those published in the literature from more qualitative studies.
Adolescent↗
The accuracy of fast phylogenetic methods for large datasets.
Whole-genome phylogenetic studies require various sources of phylogenetic signals to produce an accurate picture of the evolutionary history of a group of genomes. In particular, sequence-based reconstruction will play an important role, especially in resolving more recent events. But using sequences at the level of whole genomes means working with very large amounts of data--large numbers of sequences--as well as large phylogenetic distances, so that reconstruction methods must be both fast and robust as well as accurate. We study the accuracy, convergence rate, and speed of several fast reconstruction methods: neighbor-joining, Weighbor (a weighted version of neighbor-joining), greedy parsimony, and a new phylogenetic reconstruction method based on disk-covering and parsimony search (DCM-NJ + MP). Our study uses extensive simulations based on random birth-death trees, with controlled deviations from ultrametricity. We find that Weighbor, thanks to its sophisticated handling of probabilities, outperforms other methods for short sequences, while our new method is the best choice for sequence lengths above 100. For very large sequence lengths, all four methods have similar accuracy, so that the speed of neighbor-joining and greedy parsimony makes them the two methods of choice.
Amino Acid Sequence↗
Grading referrals to specialist breast units. Communication has been degraded to exchange of dataset.
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Breast Neoplasms↗
In search of quality--people and processes towards a unified dataset.
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Anesthesiology↗
Does a state level acute hospital admitted patient dataset encapsulate appropriate performance measures of a process of care?
Strategically there is a need to not only take a clinical process view of health care delivery but also identify the appropriate information to support the processes. When considering the clinical process view, the challenge for continuous quality improvement is to eliminate inappropriate process steps, and continuously document performance/outcome. The questions are what performance measures are useful, and does a state level data collection capture relatable measures of a process of care.
Databases, Factual↗
Visualization of large datasets in intensive care.
At the "Institut für Anaesthesiologie der Ludwig-Maximilians-Universität" in Munich a computer-based system for the analysis and interpretation of renal function and fluid and electrolyte metabolism of critical care patients has been developed. This paper describes requirements and implementation aspects of the presentation of data to the physician. Key issue is, how to transform the enormous--and, as we all know, constantly increasing--amount of plain data available in modern intensive care units (ICUs) into relevant information which can be easily turned into therapeutic actions. These issues have been discussed in literature extensively over many years, but with the upcoming of moderately priced, though powerful graphical UNIX workstations an extended functionality is feasible.
Artificial Intelligence↗
Surveillance of sexually transmitted infections in the West Midlands using anonymised individual patient datasets from genitourinary medicine clinics.
Sexually transmitted infections (STIs) declined in the UK during the 1980s and early 1990s but have increased substantially since 1995. Within the overall increase there are important differences in the epidemiology of these infections. The current, aggregate system of STI data collection in the UK provides limited demographic information and is unable to fully explain these differences. More useful information can be obtained using an enhanced surveillance system that collects disaggregate, anonymised, individual patient data including ethnic group and truncated postcode of residence. Such a system has been set up in the West Midlands NHS region. The methodology of the project is described here along with the findings to date. These findings confirm that the burden of STIs disproportionately affects young persons, men who have sex with men, black ethnic minority groups and those living in urban areas. Identifying the groups at greatest risk in this way enables interventions to be more usefully targeted.
Adolescent↗
Rates and external causes of blunt head trauma in Ontario: analysis and review of Ontario Trauma Registry datasets.
Contemporary studies of blunt head trauma and its determinants are important for prevention. It is also important to understand the strengths and limitations of the common sources of data used for the ongoing study of these injuries. Using the Ontario Trauma Registry, we described frequent patterns of blunt head trauma and identified priorities for prevention and research. A review of methodological issues that arose during the analysis of these trauma registry data is also provided. Blunt head trauma cases were identified within two data sets of the Ontario Trauma Registry. The Minimal Data Set is population-based and contains acute care injury hospitalizations, and the Comprehensive Data Set contains "major injuries" treated at a lead trauma hospital. Injury control priorities varied by age group, sex and data set and these are profiled in the manuscript. The results indicate the importance of examining multiple sources of surveillance data in establishing injury control priorities. The methodological review demonstrated the need to critically examine the completeness and accuracy of trauma registry data in arriving at decisions about priorities.
Adolescent↗
CT angiography: principles, techniques and study optimization using 16-slice multidetector CT with isotropic datasets and 3D volume visualization.
Significant advances in computed tomography (CT) scanner technology as well as 3D imaging software and hardware have resulted in amazing improvements in CT imaging of blood vessels. CT angiography has now been incorporated into daily practice and in may cases has replaced conventional angiography. CT angiography has also resulted in new applications for CT such as coronary angiography. This article discusses the current state of the art of 3D CT angiography and reviews the literature. Extensive case examples are included.
Angiography↗
Virtual acupuncture human based on chinese visible human dataset.
In this paper, we present our application of latest information technology in assisting the Chinese acupuncture research. Having integrated the Chinese Visible Human (CVH) data, virtual reality, visualization and imaging techniques, we have constructed a 3-dimensional digital human model for acupuncture. This model integrates the meridian positioning, acupoint positioning, arbitrary cutting-plane visualization, multi-layer dissection, needle puncturing simulation, as well as the common diseases-therapy information. Our work can be widely applied to Chinese acupuncture education, clinical usage and scientific research.
Acupuncture↗
New PHLS Salmonella dataset.
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Clinical Laboratory Information Systems↗
A multivariate procedure for identifying correlations between diagnoses and over-the-counter products from historical datasets.
A general problem in biosurveillance is finding the optimal aggregates of more basic data to monitor for the detection of disease outbreaks. We developed a multivariate procedure for identifying the set of over-the-counter (OTC) healthcare products that correlates best with a set of diagnoses. To ensure that the procedure produces results that agree with clinical knowledge of diseases and (OTC) products, we applied it to a set of products and set of diagnoses for which the correlation was known to be high. Our hypothesis was that the model could achieve parsimony in the set of diagnoses that correlate with sales of pediatric electrolytes while still producing a high correlation. The procedure narrowed the set of diagnoses that correlate with pediatric electrolytes from 51 diagnoses to eight diagnoses. The correlation of the set of 51 diagnoses with electrolyte sales was 0.95 and the correlation of the set of 8 diagnoses with electrolytes was 0.96. We conclude that the procedure functions as intended and is suitable for further testing with other problems in finding optimal aggregates of OTC products, and more generally of other types of biosurveillance data, to monitor for the detection of various disease outbreaks.
Commerce↗
[Reports of waiting list data from hospitals to the central registry--a database for reducing hospital waiting lists. Minimum dataset of waiting list parameters].
The governmental regulations concerning registration of waiting lists and priority of patients, laid down in July 1990, introduce a "waiting time guarantee" which ensures a waiting time not exceeding six months for patients suffering from diseases having severe impacts on health. Hospitals that are unable to treat these patients within six months are requested to refer them to other hospitals before the deadline. All hospitals have to make monthly reports of waiting list parameters to a Central Waiting List Register, enabling both a nationwide waiting list survey and comparisons between different hospitals and different counties. An online communication facility to the central register enables searches for and reporting of vacant treatment capacity.
Databases, Factual↗
Unlocking datasets.
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Costs and Cost Analysis↗