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At least 577 records · Page 32Linked to original sources
PubMed1979

A data analysis microcomputer package (DAMP) for biomedical signals.

The advent of cheap, powerful microcomputer systems makes the analysis of data via sophisticated techniques available to the personnel who are non-specialists in computing systems. The DAMP package described here is intended for use on personal computers and has therefore been written in BASIC for portability. The analysis techniques are powerful, comprising algorithms to perform sample-data generation, plotting displays, digital data filtering, auto-correlation functions, fast Fourier transforms and autoregressive modelling. The last technique contains a number of options including the display of z-plane plots, frequency response of the model, residual plotting and auto-correlation of the residuals. Illustrative results are shown from psychological mood data and rat locomotor activity. The package is designed both to instruct a user in the techniques of spectral analysis, and also to provide a range of methods for investigating time and frequency behaviour of biomedical data.

Biomedical Engineering↗
PubMed2003

Comprehensive graphic-based display of clinical pathology laboratory data.

In this age of ever-increasing demands for and uses of patient data, technologic advancements in the form of electronic patient records permit improved data access and prompt retrieval of higher quality patient care data, with more versatility in display, facilitating the integration of information concerning patients over time and between settings of care, which is in turn more accessible for use by practitioners and provides more efficient and effective decision support in areas of patient care. The graphic display of laboratory data is central to the evolving computerized patient record and needs to be taken into careful consideration along with clinician perception and ease of data interpretation in redesigning the graphic reporting of numeric clinical pathology laboratory data. An ideal system should generate user-friendly, graphic-based comprehensive reports highlighting abnormalities with trends for diagnosis, clinical management, and risk-factor detection.

Clinical Chemistry Tests↗
PubMed1991

Observations on maximum entropy processing of MR images.

A maximum entropy (MAXENT) criteria for MR image processing optimizations has previously shown poor performance, but this note observes that there are two entirely different kinds of "data transmission" applications which appear to have been intermixed. In the two cases, "image entropy" actually refers to different kinds of data variables. The previous literature formulations are for transfer of data in which pixel-locations are the transmitted variable, and these pixels may be neither uniform nor constant. The second application concerns the MRI data set for display. Its data variables are image pixel-values of magnetization intensity, and the data transfer mode has the sense of visual display. When MAXENT criteria are modified to address an array of pixel-value intensities, and use a pixel-value information entropy rather than pixel-locations entropy, then successful data processing results. Restoring display visualization from highly nonuniform surface coils for lumbar spine scans are demonstrated, as an example of MAXENT usefulness.

Image Processing, Computer-Assisted↗
PubMed2006

An interactive stereoscopic display for cooperative work--volume visualization and manipulation with multiple users.

A stereoscopic display table for cooperative work with a volume data is described. Adequate stereoscopic image generated from the volume data is displayed and shared by multiple users. All the users can observe and interact with the volume data displayed on the IllusionHole in a face-to-face environment. It displays each pair of stereoscopic images such that all users observe the 3D image at exactly the same position. An outline of the system is described in this paper.

Depth Perception↗
PubMed1979

DIODA: delineation and feature extraction of microscopical objects.

A computer program is described for delineation and measurement of microscopical objects, such as cells and chromosomes, which may have been scanned using absorbance, fluorescence or reflectance microscopy. The quality of the object delineation is optimized through the controur ratio, which is simply computed from the object contour. Geometrical features, like the perimeter and area are computed. A new definition is introduced for the background region, especially suited for the analysis of closely packed objects. This definition is based upon a comparison between total staining material content values resulting from a variety of methods and circumstances. The program is principally intended for use in the on-line real-time environment of a small laboratory computer, but may be used off-line as well. It has facilities for displaying the results and the process by which they are produced. A program module is described for displaying scan data on a bilevel display using an adaptation of the sigma-delta method.

Computers↗
PubMed2003

The employment of an iterative design process to develop a pulmonary graphical display.

OBJECTIVE: Data representations on today's medical monitors need to be improved to advance clinical awareness and prevent data vigilance errors. Simply building graphical displays does not ensure an improvement in clinical performance because displays have to be consistent with the user's clinical processes and mental models. In this report, the development of an original pulmonary graphical display for anesthesia is used as an example to show an iterative design process with built-in usability testing. DESIGN: The process reported here is rapid, inexpensive, and requires a minimal number of subjects per development cycle. Three paper-based tests evaluated the anatomic, variable mapping, and graphical diagnostic meaning of the pulmonary display. MEASUREMENTS: A confusion matrix compared the designer's intended answer with the subject's chosen answer. Considering deviations off the diagonal of the confusion matrix as design weaknesses, the pulmonary display was modified and retested. The iterative cycle continued until the anatomic and variable mapping cumulative test scores for a chosen design scored above 90% and the graphical diagnostic meaning test scored above 75%. RESULTS: The iterative development test resulted in five design iterations. The final graphical pulmonary display improved the overall intuitiveness by 18%. The display was tested in three categories: anatomic features, variable mapping, and diagnostic accuracy. The anatomic intuitiveness increased by 25%, variable mapping intuitiveness increased by 34%, and diagnostic accuracy decreased slightly by 4%. CONCLUSION: With this rapid iterative development process, an intuitive graphical display can be developed inexpensively prior to formal testing in an experimental setting.

Anesthesia, General↗
PubMed1992

EIS (executive information systems): a better way to view hospital trends.

Executive information systems (EIS) are changing the way managers and executives view information. EIS is a work-station based information system that integrates information from the important parts of a healthcare organization to give executives a high-level perspective on key performance indicators and trends affecting their institutions. Such systems employ graphics and color to display real-time data in a format that is easily interpreted by executives and that helps them make better decisions. EIS technology is particularly appropriate for disseminating and highlighting financial information. However, for such systems to work effectively and for executives to obtain the greatest benefits from them, financial managers must help establish and promote EIS.

Color↗
PubMed1999

Clinical informatics: 2000 and beyond.

Healthcare has begun to flounder in the mounting flood of data available from automated monitoring equipment, microprocessor controlled life-support equipment, such as ventilators, ever more sophisticated laboratory tests, and the myriad of minor technological wonders that every hospital and clinic seem to collect. It is no longer enough to merely display the data in a large spreadsheet or on a complex, colorful time-sequence graph. The next generation of healthcare information systems must help the clinician to assimilate the myriad of data and to make fast and effective decisions. The following is a list of features that the next generation of computer systems will have to include if they are to have a significant impact on the quality of patient care: data acquisition, data storage, information display, data processing, and decision support. By automating or streamlining repetitive or complex tasks, correlating and presenting complex and potentially confusing data, and tracking patient outcomes, the computer can augment clinicians' skills to improve patient care.

Computer Systems↗
PubMed1998

Informative presentation of summary data.

Many research reports display summary data on study subjects. Seemingly simple tables of data present the mean and standard deviation for each variable. However, this method of presentation is sometimes less than helpful and at other times it is plain wrong. Ordinal data should not be summarized using means and standard deviations and even interval data are often best not summarized in this way. Medians and percentiles are usually more informative. This article, the first in a series, outlines some pitfalls in describing study subjects and advises how to avoid them.

Analysis of Variance↗
PubMed1979

Interactive display and analysis of data from bivariate flow cytometers.

An interactive computer program, SWELL, displayss and analyzes bivariate distributions generated by flow cytometers. SWELL is modular with options available via a menu, is written in Fortran, and utilizes a video color display system. Data are accumulated as a bivariate distribution that is transferred to the computer as a 64 x 64 matrix. For ease of visualization, matrices are displayed in pseudocolor. The distribution values are broken into eight ranges and each range is represented by a color. Each element of the matrix is then displayed in its assigned color. To allow pooling and comparison, distributions are aligned, edited, and standardized. Unknown samples are pooled or analyzed singly and compared to the normal pool by subtraction. Differences are displayed as pseudocolor matrices of sign, magnitude, or statistical magnitude in units of standard deviation. This latter display, scaled to tolerance limits, readily reveals regions of significant difference between normal and abnormal samples. Counts within such regions can be compared to diagnose samples automatically.

Cervix Uteri↗