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Biomedical subjects

Donny Tjandra

Publications and source records attributed to Donny Tjandra.

5 recordsLinked to original sources

A neuroinformatics database system for disease-oriented neuroimaging research.

Clinical databases are continually growing and accruing more patient information. One of the challenges for managing this wealth of data is efficient retrieval and analysis of a broad range of image and non-image patient data from diverse data sources. This article describes the design and implementation of a new class of research data warehouse, neuroinformatics database system (NIDS), which will alleviate these problems for clinicians and researchers studying and treating patients with intractable temporal lobe epilepsy. The NIDS is a secured, multi-tier system that enables the user to gather, proofread, analyze, and store data from multiple underlying sources. In addition to data management, the NIDS provides several key functions including image analysis and processing, free text search of patient reports, construction of general queries, and on-line statistical analysis. The establishment of this integrated research database will serve as a foundation for future hypothesis-driven experiments, which could uncover previously unsuspected correlations and perhaps help to identify new and accurate predictors for image diagnosis.

Biomedical Research↗

DBMap: a space-conscious data visualization and knowledge discovery framework for biomedical data warehouse.

Advances in digital imaging modalities as well as other diagnosis and therapeutic techniques have generated a massive amount of diverse data for clinical research. The purpose of this study is to investigate and implement a new intuitive and space-conscious visualization framework, called DBMap, to facilitate efficient multidimensional data visualization and knowledge discovery against the large-scale data warehouses of integrated image and nonimage data. The DBMap framework is built upon the TreeMap concept. TreeMap is a space constrained graphical representation of large hierarchical data sets, mapped to a matrix of rectangles, whose size and color represent interested database fields. It allows the display of a large amount of numerical and categorical information in limited real estate of the computer screen with an intuitive user interface. DBMap has been implemented and integrated into a large brain research data warehouse to support neurologic and neuroradiologic research at the University of California, San Francisco Medical Center. For imaging specialists and clinical researchers, this novel DBMap framework facilitates another way to better explore and classify the hidden knowledge embedded in medical image data warehouses.

Algorithms↗

A web-based federated neuroinformatics model for surgical planning and clinical research applications in epilepsy.

There is an increasing need to efficiently share diverse clinical and image data among different clinics, labs, and departments of a medical center enterprise to facilitate better quality care and more effective clinical research. In this paper, we describe a web-based, federated information model as a viable technical solution with applications in medical refractory epilepsy and other neurological disorders. We describe four such online applications developed in a federated system prototype: surgical planning, image analysis, statistical data analysis, and dynamic extraction, transforming, and loading (ETL) of data from a heterogeneous collection of data sources into an epilepsy multimedia data warehouse (EMDW). The federated information system adopts a three-tiered architecture, consisting of a user-interface layer, an application logic layer, and a data service layer. We implemented two complementary federated information technologies, i.e., XML (eXtensible Markup Language) and CORBA (Common Object Request Broker Architecture), in the prototype to enable multimedia data exchange and brain images transmission. The preliminary results show that the federated prototype system provides a uniform interface, heterogeneous information integration and efficient data sharing for users in our institution who are concerned with the care of patients with epilepsy and who pursue research in this area.

Animals↗

An XML message broker framework for exchange and integration of microarray data.

MOTIVATION: Microarrays are an important research tool for the advancement of basic biological sciences. However this technology has yet to be integrated with clinical decision making. We have implemented an information framework based on the Microarray Gene Expression Markup Language (MAGE-ML) specification. We are using this framework to develop a test-bed integrated database application to identify genomic and imaging markers for diagnosis of breast cancer. RESULTS: We developed extensible software architecture for retrieving data from different microarray databases using MAGE-ML and for combining microarray data with breast cancer image analysis and clinical data for correlation studies. The framework we developed will provide the necessary data integration to move microarray research from basic biological sciences to clinical applications. AVAILABILITY: Open source software will be available from SourceForge (http://sourceforge.net/projects/microsoap/).

Database Management Systems↗

Workflow-enabled distributed component-based information architecture for digital medical imaging enterprises.

Few information systems today offer a flexible means to define and manage the automated part of radiology processes, which provide clinical imaging services for the entire healthcare organization. Even fewer of them provide a coherent architecture that can easily cope with heterogeneity and inevitable local adaptation of applications and can integrate clinical and administrative information to aid better clinical, operational, and business decisions. We describe an innovative enterprise architecture of image information management systems to fill the needs. Such a system is based on the interplay of production workflow management, distributed object computing, Java and Web techniques, and in-depth domain knowledge in radiology operations. Our design adapts the approach of "4+1" architectural view. In this new architecture, PACS and RIS become one while the user interaction can be automated by customized workflow process. Clinical service applications are implemented as active components. They can be reasonably substituted by applications of local adaptations and can be multiplied for fault tolerance and load balancing. Furthermore, the workflow-enabled digital radiology system would provide powerful query and statistical functions for managing resources and improving productivity. This paper will potentially lead to a new direction of image information management. We illustrate the innovative design with examples taken from an implemented system.

Computer Communication Networks↗