Episode creation is the task of classifying medical events and related clinical data to high-level concepts, such as diseases. Challenges in episode creation result in part because of data, in the patient record, only implicitly being associated with their respective episodes. Furthermore, traditional approaches have been limited to using feature-poor claims records to generate episodes. The accurate correlation of data to their episodes is valuable in health outcomes research to discern resource utilization with respect to medical conditions. This paper describes a combinatorial optimization approach for constructing episodes, which supports the incorporation of heterogeneous data types. Aspects of this approach include an episode model for characterizing the generation of data elements as a result of a process, a methodology for identifying the relationships between implicit processes and the data elements generated by the processes, a measure for evaluating candidate episode configurations, and an energy-minimization methodology for addressing episode creation. An implementation of this work, called Episode Creation Version 2 (EC2), has been applied on patient records with various episode types, which present with knee pain. EC2 demonstrated data element classification precision and recall scores of 78% and 82%, respectively. Significant improvements in precision and recall were observed over a traditional healthcare services approach.

Search engines, such as Google, assign scores to news articles based on their relevancy to a query. However, not all relevant articles for the query may be interesting to a user. For example, if the article is old or yields little new information, the article would be uninteresting. Relevancy scores do not take into account what makes an article interesting, which would vary from user to user. Although methods such as collaborative filtering have been shown to be effective in recommendation systems, in a limited user environment there are not enough users that would make collaborative filtering effective. We present a general framework for defining and measuring the "interestingness" of articles, incorporating user-feedback. We show 21% improvement over traditional IR methods

We introduce multiple topic tracking (MTT) for iScore to better recommend news articles for users with multiple interests and to address changes in user interests over time. As an extension of the basic Rocchio algorithm, traditional topic detection and tracking, and single-pass clustering, MTT maintains multiple interest profiles to identify interesting articles for a specific user given user-feedback. Focusing on only interesting topics enables iScore to discard useless profiles to address changes in user interests and to achieve a balance between resource consumption and classification accuracy. Also by relating a topic's interestingness to an article.s interestingness, iScore is able to achieve higher quality results than traditional methods such as the Rocchio algorithm. We identify several operating parameters that work well for MTT. Using the same parameters, we show that MTT alone yields high quality results for recommending interesting articles from several corpora. The inclusion of MTT improves iScore's performance by 9% in recommending news articles from the Yahoo! News RSS feeds and the TREC11 adaptive filter article collection. And through a small user study, we show that iScore can still perform well when only provided with little user feedback.

Quantitative image analysis (QIA) goes beyond subjective visual assessment to provide computer measurements of the image content, typically following image segmentation to identify anatomical regions of interest (ROIs). Commercially available picture archiving and communication systems focus on storage of image data. They are not well suited to efficient storage and mining of new types of quantitative data. In this paper, we present a system that integrates image segmentation, quantitation, and characterization with database and data mining facilities. The paper includes generic process and data models for QIA in medicine and describes their practical use. The data model is based upon the Digital Imaging and Communications in Medicine (DICOM) data hierarchy, which is augmented with tables to store segmentation results (ROIs) and quantitative data from multiple experiments. Data mining for statistical analysis of the quantitative data is described along with example queries. The database is implemented in PostgreSQL on a UNIX server. Database requirements and capabilities are illustrated through two quantitative imaging experiments related to lung cancer screening and assessment of emphysema lung disease. The system can manage the large amounts of quantitative data necessary for research, development, and deployment of computer-aided diagnosis tools.

Prefetching methods have traditionally been used to restore archived images from picture archiving and communication systems to diagnostic imaging workstations prior to anticipated need, facilitating timely comparison of historical studies and patient management. The authors describe a problem-oriented prefetching scheme, detailing 1) a mechanism supporting selection of patients for prefetching via characterizations of clinical problems, using multiple data sources (picture archiving and communication systems, hospital information systems, and radiology information systems), classifying patients into cohorts on the basis of their medical conditions (e.g., lung cancer); and 2) prefetching of multimedia data (imaging, laboratory, and medical reports) from clinical databases to enable the viewing of an integrated patient record. Preliminary evaluation of the prefetching algorithm using classic information retrieval measures showed that the system had high recall (100 percent), correctly identifying and retrieving data for all patients belonging to a target cohort, but low precision (50 percent). A key finding during testing was that the recall of the system was increased through the use of multiple data sources (compared with one data source), because of better patient descriptors. Medical problems and patient cohorts were more specifically defined by combining information from heterogeneous databases.

A knowledge-based approach to retrieve medical images by feature and content with spatial and temporal constructs is developed. Selected objects of interest in an image are segmented and contours are generated. Features and content are extracted and stored in a database. Knowledge about image features can be expressed as a type abstraction hierarchy (TAH), the high-level nodes of which represent the most general concepts. Traversing TAH nodes allows approximate matching by feature and content if an exact match is not available. TAHs can be generated automatically by clustering algorithms based on feature values in the databases and hence are scalable to large collections of image features. Since TAHs are generated based on user classes and applications, they are context- and user-sensitive. A knowledge-based semantic image model is proposed to represent the various aspects of an image object's characteristics. The model provides a mechanism for accessing and processing spatial, evolutionary and temporal queries. A knowledge-based spatial temporal query language (KSTL) has been developed that extends ODMG's OQL and supports approximate matching of features and content, conceptual terms and temporal logic predicates. Further, a visual query language has been developed that accepts point-click-and-drag visual iconic input on the screen that is then translated into KSTL. User models are introduced to provide default parameter values for specifying query conditions. We have implemented the KMeD (Knowledge-based Medical Database) system using these concepts.

This paper describes a unified data model that represents multimedia, timeline, and simulation data utilizing a single set of related data modeling constructs. A uniform model for multimedia types structures image, sound, video, and long text data in a consistent way, giving multimedia schemas and queries a degree of data independence even for these complex data types. Information that possesses an intrinsic temporal element can all be represented using a construct called a stream. Streams can be aggregated into parallel multistreams, thus providing a structure for viewing multiple sets of time-based information. The unified stream construct permits real-time measurements, numerical simulation data, and visualizations of that data to be aggregated and manipulated using the same set of operators. Prototypes based on the model have been implemented for two medical application domains: thoracic oncology and thermal ablation therapy of brain tumors. Sample schemas, queries, and screenshots from these domains are provided. Finally, a set of examples is included for an accompanying visual query language discussed in detail in another document.

PICQUERY/sup +/, a high-level domain-independent query language for pictorial and alphanumeric database management, is introduced. The PICQUERY/sup +/ language and its underlying stacked image data model are enhanced with major advances that include: convenient specification of the data domain space among a multimedia database federation, visualization of underlying data models, knowledge-based hierarchies, and domain rules, understanding of high-level abstract data types, ability to perform data object matches based on imprecise or fuzzy descriptors, imprecise relational correlators, and temporal and object evolutionary events, specification of alphanumeric and image processing algorithms on data, and specification of alphanumeric and image visualization methods for user presentation. The power of PICQUERY/sup +/ is illustrated using examples drawn from the medical imaging domain. A graphical menu-driven user interface is demonstrated for this domain as an example of the menu interface capabilities of PICQUERY/sup +/.>

New problems of updating views involving inter-entity relationships or joins are identified, beyond those reported previously in the literature. A general purpose method and a set of algorithms are presented for correctly decomposing multilingual update requests on a network of distributed heterogeneous databases. The method and algorithm also apply to both homogeneous nondistributed and distributed database environments. The method, called prototype views and update rules, applies to individual relationships in an entity relationship (ER) view of the network database and gives a floorplan for update decomposition. The network database view represents a unified conceptual view of all the individual databases in the heterogeneous network (i.e. of the objects shared across the network). The update request is decomposed into a sequence of intermediate control language steps to subsequently guide the particular updates to each of the underlying databases in the network. Individual database updates are performed by each particular database management system (DBMS).>

A reasonably comprehensive set of data accessing and manipulation operations that should be supported by a generalized pictorial database management system (PDBMS) is proposed. A corresponding high-level query language, PICQUERY, is presented and illustrated through examples. PICQUERY has been designed with a flavor similar to QBE as the highly nonprocedural and conservational language for the pictorial database management system PICDMS. PICQUERY and a relational QBE-like language would form the language by which a user could access conventional relational databases and at the same time pictorial databases managed by PICDMS or other robust PDBMS. This language interface is part of an architecture aimed toward data heterogeneity transparency over pictorial and nonpictorial databases.>

The collection and processing of digital image or pictorial data based on photographs, drawings, maps, etc. is undergoing a period of rapid growth. Industry, universities, and governmental and military agencies are producing an ever increasing volume and variety of such data. For many years special image data handling systems have been developed to store and retrieve specific types of pictorial data. More recently, however, it has been realized that instead of the one-of-its-kind type of approach, the generalized pictorial data base management system approach is the preferred approach (much in the same way that today's DBMS for record-type data are unquestionably preferred in most eases over tailor-made one-of-its kind systems).

The proliferation of different DBMS and advances in computer networking and communications have led to increasing heterogeneous distributed DBMS network scenarios. Major heterogeneity problems and challenges include: different database models, syntactically and semantically different DBMS, different types of controls (recovery, etc.), etc. We address herein the long-range goal for a heterogeneous distributed DBMS (HD-DBMS) to be able to support a network in which any user in any node can be given an integrated and tailored view or schema, while in reality the data may reside in one single database or in physically separated databases, managed individually by the same type of DBMS (by the only one the user understands) or by different DBMS. We cite the major approaches to data sharing and accessing: from the primitive commercial file and database unload/load and PC download, to common interfaces on top of existing DBMS, to the R&D and prototype efforts toward the long-range desires. Commercial availability of the more encompassing thrusts may become a reality with the mounting problems, opportunity costs, and demand for data sharing in the heterogeneous world. Major research and development projects in this arena are leading toward some partial attainment of the long-range objective. The UCLA HD-DBMS project is highlighted herein, with a presentation of its status, progress, and plans. It is a longer range project, with the unique feature of allowing any user in the network to use a preferred database model and DML to access or update any data in the heterogeneous network. HD-DBM5 is to provide a multilingual interface to heterogeneous distributed databases.

An architectural approach and a software mechanism is presented to enhance the auditability and testability of advanced transaction processing EDP systems. A high degree of auditability can be achieved through integrated support of auditability mechanisms as opposed to the traditional after-the-fact, ad hoc, add-on audit and test approaches. A programmable audit evidence gathering mechanism called an audit probe is proposed. A generic model of the audit probe is presented and its major features outlined. Audit hooks are proposed as standard probe interfaces for audit software. An overview of a high level audit-oriented audit probe definition language (APDL) for specifying the evidence gathering requirements for audit is highlighted. Audit test concurrent with the normal operation of the system and the capability of filtering only selected audit data are advocated. An example is presented illustrating the use of APDL and its value to auditing and quality control.

Fault-tolerance is systematically applied to the organization of a parallel associative (content addressable) database processor. Storage areas are protected by duplication and by error detecting and/or correcting codes. A duplex Checking Unit is introduced to check the reading and writing operations. Individual Area Processors are employed to search the storage areas. They are protected by duplexing or triplexing with or without sparing. Effectiveness of these fault-tolerance techniques is assessed by means of reliability predictions for a 100-storage area system. The UCLA ARIES reliability modeling program is employed to obtain the reliability predictions. Major gains in system reliability are demonstrated, and relative effectiveness of alternate approaches is analyzed.

The database structure and data manipulation capabilities of a generalized PICture Database Management System (PICDMS) are presented. They are based on a dynamic, stacked-image, logical database structure that uses gridded, rather than topological, data representation. A prototype PICDMS has been designed and implemented. A commercial version is being used as a generator of image processing programs. The system has novel capabilities for nonprogrammer users: it is able to 1) build multiple-variable databases from photographs and other two-dimensional data sources such as maps, drawings, etc., and 2) manipulate such data using simple logical commands. Physical organization and accessing strategies are outlined. A summary of the PICDMS data manipulation capabilities is presented and a subset of operations is illustrated with brief examples. A comprehensive example displays PICDMS capabilities and the programming advantages it possesses over other approaches.

This paper presents the characteristics of scientific remotely-sensed databases that are relevant to --- and pose unique challenges for --- general-purpose database management systems (DBMSs). We describe a prototype system that integrates geophysical data and its metadata from both satellite and in situ sources, using a relational general-purpose DBMS to manage the catalog and observational data, and a video optical disk to archive images. Based upon our experience with this application, we suggest augmentations to DBMSs that would facilitate their use not only for scientific databases, but also for engineering, document, and even commercial database applications.

The need for robust recovery facilities in modern database management systems is quite well known. Various authors have addressed recovery facilities and specific techniques, but none have delved into the problem of recovery in database machines. In this paper, the types of undesirable events that occur in a database environment are classified and the necessary recovery information, with subsequent actions to recover the correct state of the database, is summarized. A model of the “processor-per-track” class of parallel associative database processor is presented. Three different types of recovery mechanisms that may be considered for parallel associative database processors are identified. For each architecture, both the workload imposed by the recovery mechanisms on the execution of database operations (i.e., retrieve, modify, delete, and insert) and the workload involved in the recovery actions (i.e., rollback, restart, restore, and reconstruct) are analyzed. The performance of the three architectures is quantitatively compared. This comparison is made in terms of the number of extra revolutions of the database area required to process a transaction versus the number of records affected by a transaction. A variety of different design parameters of the database processor, of the database, and of a mix of transaction types (modify, insert, and delete) are considered. A large number of combinations is selected and the effects of the parameters on the extra processing time are identified.

Doubly-chained tree data base (file) structures are analysed and modelled, taking into account realistic implementation-oriented factors. Formulations for average access time and storage requirements are derived, showing the effect on performance and the interrelation of the characteristics of the contents of the data base, the complexity of the queries, storage device characteristics and processing times, and implementation-oriented (e.g. storage mapping) alternatives. Performance results are obtained from these models for six real life data bases. The doubly-chained alternatives are compared and evaluated to provide practical design guidelines and strategies.

Powerful data structures for interactive graphics systems are tediously intricate, and are indeed difficult to program, debug, maintain and modify. A simple data structure is presented to represent two- and three-dimensional objects. One of its great benefits is its ease of implementation and maintenance. Although because of its simplicity various facilities provided by more complex data structures are not available, it can be an attractive basis for a class of graphics systems, such as the operational interactive design/drafting system outline.