The NRC report. Is healthcare ready for the Internet?
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Forecasting↗
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Results for “Medical Informatics Computing”
Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
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Agent-oriented captology for medical informatics.
Considering that neither captology nor agent-orientation, are applied in medical informatics, as they could be, the paper presents a broad-spectrum generic architectural framework to support developing adaptive medical applications, based on synergistic correlation between persuasive interfaces and intelligent agents. Their main features are adapted for medical informatics. Lying on this groundwork, the design space for agent-oriented persuasive applications is defined and several guidelines for its main dimensions are given. The approach is instantiated through an agent-based test-bench application, having the purpose to persuade to quit smoking.
Artificial Intelligence↗
Medical informatics education for "allied" profiles.
Medical informatics education should be adapted for each speciality of "allied professions". In this paper we try to share from our experience with students of several profiles: medicine, dentistry, pharmacy, physio-kineto-therapy, clinical laboratory, dentistry techniques and stomatological prophylaxis.
Allied Health Personnel↗
Can we classify medical data dictionaries?
Medical Data Dictionaries enable a clinical information system to maintain a controlled vocabulary, to store descriptive knowledge about terms, to map between those terms and from those terms to external classifications. They support a variety of functions in the information system, ranging from structured documentation to knowledgebased functions. This paper derives a multi-axial classification for medical data dictionaries. Dictionaries are classified along 4 axes, a vocabulary axis defining vocabulary properties, an application axis which characterises the degree of linkage between dictionary and information system, a semantic axis defining the quality of inter-term relationships and finally a language axis which classifies rules for inter-term relationships in semiotic theory. As an example two existing dictionaries are classified in the model and reference is taken to the design of future dictionaries.
Artificial Intelligence↗
Biointelligence age: implications for the future of medicine.
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Artificial Intelligence↗
A model and application for estimating completeness of registration.
Completeness of population-based registration systems is recognized to be an important aspect of the quality of information in registries which has to be examined. In this paper a model is presented which was used to estimate completeness of reporting of Down syndrome data notified to the Styrian Malformation registry between 1985-92. The model introduced is based on the two-source capture-recapture method allowing for time-varying parameters. For estimation of the parameters a discrete-time filtering algorithm was developed. For the used data set, an estimate of completeness derived from this model was in good agreement with an independent estimator based on demographic data and maternal age-specific Down syndrome risks whereas the usual two-source capture-recapture method gave a higher estimate.
Algorithms↗
Information processing in healthcare at the start of the third Millennium: potential and limitations.
The 21st century is said to be a century of the information society. We should be aware that continuing progress in information processing methodology (IPM) and information and communication technology (ICT) is changing our societies, including medicine and health care. At the start of the third Millennium we should ask ourselves, what progress can we expect from modern IPM/ICT for healthcare in the coming decade, what concerns does the information society have to face, and what steps have to be taken. These questions were addressed by clinicians, researchers and industrial representatives in a panel discussion at the joint conference ISCB-GMDS-99 of the International Society of Clinical Biostatistics and the German Society for Medical Informatics, Biometry and Epidemiology. Important aspects raised by the panelists and in the subsequent discussion were: (1) the main goal of expanding IPM/ICT should be to further improve quality of care, while maintaining reasonable costs; (2) with the support of modern IPM and ICT the boundaries between inpatient and outpatient care will fade away enabling a more efficient, patient-centered health care; (3) cooperation between health-care professionals will increase; there will be different ways of communication between them and with the patient, including modern ICT and the Internet; (4) society must be concerned with achieving equal opportunities in being informed about and in using new ICT; (5) misuse of data will remain a serious problem and can become an obstacle to progress.
Biometry↗
Digital Libraries and Recent Medical Informatics Research. Findings from the IMIA Yearbook of Medical Informatics 2001.
The Yearbook of Medical Informatics is published annually by the International Medical Informatics Association (IMIA) and contains a selection of recent excellent papers on medical informatics research (http://www.med.uni-heidelberg.de/mi/yearbook/index.htm). The special topic of the just published Yearbook 2001 is "Digital Libraries and Medicine". Digital libraries have changed dramatically and will continue to change the way we work with medical knowledge. The selected papers present recent research and new results on digital libraries. As usual, the Yearbook 2001 also contains a variety of papers on other subjects relevant to medical informatics, such as Electronic Patient Records, Health Information Systems, Health and Clinical Management, Decision Support Systems, Education, as well as Image and Signal Processing. This paper will briefly introduce the contributions covering digital libraries and will show how medical informatics research contributes to this important topic.
Humans↗
On the use of EEG features towards person identification via neural networks.
Person identification based on spectral information extracted from the EEG is addressed in this work a problem that has not yet been seen in a signal processing framework. Spectral features are extracted non-parametrically from real EEG data recorded from healthy individuals. Neural network classification is applied on these features using a Learning Vector Quantizer in an attempt to experimentally investigate the connection between a person's EEG and genetically specific information. The proposed method, compared with previously proposed methods, has yielded encouraging correct classification scores in the range of 80% to 100% (case-dependent). These results are in agreement with previous research showing evidence that the EEG carries genetic information.
Adult↗
[Future outlook for LAS, LIS].
In Japan, the application of LAS/LIS was started in some hospitals in the 1970's. Thereafter, these systems rapidly developed, becoming established in new national medical university hospitals in the late 1970's, referring to the system introduced in the central laboratory of each hospital. Currently, the LAS/LIS application system is employed in the central laboratory. In addition, this system provides diagnostic information based on laboratory data, responds to various questions regarding clinical examinations, develops strategies for controlling hospital infection using the infection control system, and provides information on the appropriate use of antimicrobial agents. In the future, this system may become even more useful. In this study, we reviewed the current status and issues of the mutual utilization of medical information among medical institutions to achieve further advances.
Clinical Laboratory Information Systems↗
Eyeing IT trends and challenges. To predict healthcare's future, look at the industry's current business environment.
General health care industry business objectives and goals drive technology implementation within the hospital setting.
Confidentiality↗
[Specialized applications and information systems].
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Computers↗
Communication of information in the homecare context.
Organizing the Homecare with new information technologies is nowadays an important challenge. Indeed, some medical evolutions as the improvement of the duration of life, the number of chronic diseases and some social evolutions, such as the quality of patient life, or economic evolutions, such as the reduction of hospitalisation costs, could benefit from homecare. In this paper, we present the problem of the communication of information in the homecare context. Some main phases have been described that compose the two homecare processes: a logistic process and a care process. The communication of information during homecare depends on the concerned phases: first, some exchanges of information from existing Information System to the Homecare Information System; then, some exchanges between the homecare system and the mobile health care actors; and then, some mails during the outcome phase. Coordination architecture is briefly described, and two different implementations for the communication of information during homecare are presented: one is using XML messages to exchange information between Information Systems; the other is using mobile tools for communicating with mobile actors.
Efficiency, Organizational↗
A preprocessing method for improving data mining techniques. Application to a large medical diabetes database.
The Knowledge Discovery in Databases (KDD) methodology seems to be attractive on the analyze of large clinical databases. In the KDD process, the preprocessing step (data cleaning and handling of missing values) is paramount since it conditions the quality of the results obtained by data mining procedures and represents about 80% of the whole project time. The aims of the present study were to analyze this step and provide tools to handle inconsistent data and missing values. We have broken down the process into 3 main stages: data cleaning--explanatory study of missing values--choice of the procedure used for handling missing values. The data cleaning stage was based on a system of logical rules to correct mistakes and on cluster analysis to discard the poorly filled files. The missing-data mechanism was analyzed by means of multivariate statistical procedures. Two methods to deal with missing values were compared: imputation by the most common value (mode) and imputation using decision trees. This study was performed on a large medical diabetes database (23,601 patients) including numerous missing values. A system of logical rules allowed to correct mistakes on essential parameters (for example, the type of diabetes). Cluster analysis allowed to identify 10% of poorly filled files. After multivariate analysis, the missing-data mechanism could be considered as random. For variables with low number of missing values (< 10%) and categories (< 4), imputation using decision trees provided better results than imputation by mode.
Data Interpretation, Statistical↗