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Results for “Data Storage And Retrieval”

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At least 343 records · Page 19Linked to original sources
PubMed2005

YPED: a proteomics database for protein expression analysis.

We have developed the Yale Protein Expression Database (YPED) to address the storage, retrieval, and integrated analysis of proteomics data generated by Yale's Keck Protein Chemistry and Mass Spectrometry Facility. YPED is Web-accessible and currently handles sample requisition, result reporting and sample comparison for ICAT, DIGE and MUDPIT samples. Sample descriptions are compatible with the evolving MIAPE standards. Peptides and proteins identified using Sequest or Mascot are validated with the Trans-Proteomic Pipeline developed at the Institute of Systems Biology and data from the resulting XML file are stored in the database. Researchers can view, subset and download their data through a secure Web interface.

Databases, Protein↗
PubMed2001

Knowledge representation and retrieval using conceptual graphs and free text document self-organisation techniques.

Hospitals generate and store a large amount of clinical data each year, a significant portion of which is in free text format. Conventional database storage and retrieval algorithms are incapable of effectively processing free text medical data. The rich information and knowledge buried in healthcare records are unavailable for clinical decision-making. We examined a number of techniques for structuring and processing free text documents to effective and efficient for information retrieval and knowledge discovery. One critical success criterion is that the complexity of the techniques must be polynomial both in space and time for them to be able to cope with very large databases. We used conceptual graphs (CG) to capture the structure and semantic information/knowledge contained within the free text medical documents. Ordering and self-organising techniques (lattice techniques and knowledge space) were used to improve organisation of concepts from standard medical nomenclatures and large sets of free text medical documents. Pair-wise union of CG was performed to identify the common generalisation structure and a lattice structure of these CG documents. A combination of all three techniques allowed us to organise a set of 9000 discharge summaries into a generalisation hierarchy that supported efficient and rich information/knowledge retrieval.

Classification↗
PubMed1978

Development of a computerised cancer data management system at the Mayo Clinic.

A multidisciplinary team was assembled to design a cancer data management system that would meet the storage, retrieval and analysis NEEDS OF Mayo's clinical trials of anti-tumour drugs. To fulfill these requirements, a computerised data entry and retrieval system was developed, the primary patient health record used by the oncologists was redesigned and the clerical procedures and work flow within the Cancer Center Statistics Office were reorganised. The end result of this project is a system that has: (1) enabled Mayo to meet its reporting requirements as a Comprehensive Cancer Center; (2) provided the statisticians and the physicians with the capacity to perform more detailed and accurate analyses of clinical trials; (3) reduced the clerical effort needed for preparing reports and analyses; (4) provided the potential for expansion to meet the growing requirements of the future and (5) attained that often elusive goal of computer systems--user satisfaction.

Antineoplastic Agents↗
PubMed1982

Microcomputer assisted interpretative reporting of protein electrophoresis data.

A microcomputer based system for interpretative reporting of protein electrophoretic data has been developed. Data for serum urine, and cerebrospinal fluid protein electrophoreses as well as immunoelectrophoresis can be entered. Patient demographic information is entered through the keyboard, followed by manual entry of total and fractionated protein levels obtained after densitometer scanning of the electrophoretic strip. Protein patterns are coded, interpreted, and final reports generated. In most cases, interpretation time is less than one second. Computer misinterpretation is uncommon and easily corrected by edit functions within the system. Discrepancies between computer and pathologist interpretation are automatically stored in a separate data file for later review and possible program modification. Any or all previous tests on a patient may be reviewed, with graphic display of the electrophoretic pattern. The system is well-accepted by the laboratory staff, and allows rapid storage, retrieval, and analysis of protein electrophoretic data.

Blood Protein Electrophoresis↗
PubMed1986

Implementation of a statewide perinatal automated medical network (PAM/NET) for Michigan.

PAM/NET is a computerized data base and conferencing system used by nine neonatal intensive care units in Michigan and Illinois. The system depends on the timesharing resource of a large university mainframe computer. The data base functions are managed by a sophisticated inverted file relational data base management system capable of mass storage and rapid and specific retrieval of individual cases or summary data. Data stored in the system are used to generate admission, discharge and developmental assessment clinic summaries that serve as such for the medical record and as letters to primary physicians. We report here the early experience in the design and dissemination of this database network to the participating hospitals. Conflicting goals of sharing and confidentiality of clinical data are addressed in the design of this system.

Ambulatory Care Facilities↗
PubMed1995

Time series migration in Britain: the context for 1991 census analysis.

"An administrative register, the National Health Service Central Register (NHSCR), is used by the Census Office (OPCS) to produce counts of NHS patients re-registering in different Family Health Service Authorities (FHSAs) in England and Wales. These movement data can be used to establish how unique or typical the migration occurring in the year prior to the Census was in relation to that for the whole decade. This paper examines national, regional and local examples of the information that can be extracted from a database system called TIMMIG that provides access to an NHSCR migration time series and a parallel series of mid-year population estimates. In advance of the publication of Special Migration Statistics, a preliminary comparison is made between the levels of in-migration to FHSA areas recorded in the NHSCR and in the 1991 Census."

Data Collection↗
PubMed1997

The Virtual Microscope.

We present the design of the Virtual Microscope, a software system employing a client/server architecture to provide a realistic emulation of a high power light microscope. We discuss several technical challenges related to providing the performance necessary to achieve rapid response time, mainly in dealing with the enormous amounts of data (tens to hundreds of gigabytes per slide) that must be retrieved from secondary storage and processed. To effectively implement the data server, the system design relies on the computational power and high I/O throughput available from an appropriately configured parallel computer.

Computers↗
PubMed1994

A review of state legislation on DNA forensic data banking.

Recent advances in DNA identification technology are making their way into the criminal law. States across the country are enacting legislation to create repositories for the storage both of DNA samples collected from convicted offenders and of the DNA profiles derived from them. These data banks will be used to assist in the resolution of future crimes. This study surveys existing state statues, pending legislation, and administrative regulations that govern these DNA forensic data banks. We critically analyzed these laws with respect to their treatment of the collection, storage, analysis, retrieval, and use of DNA and DNA data. We found much variation among data-banking laws and conclude that, while DNA forensic data banking carries tremendous potential for law enforcement, many states, in their rush to create data banks, have paid little attention to issues of quality control, quality assurance, and privacy. In addition, the sweep of some laws is unnecessarily broad. Legislative modifications are needed in many states to better safeguard civil liberties and individual privacy.

Advisory Committees↗
PubMed2026

OmniExtract: an automatic data extraction tool based on large language model and prompt engineering.

Extracting structured information from documents or scientific papers is crucial for data sharing and retrieval. Recent advances in large language models (LLMs) have demonstrated strong capabilities in language understanding, and a number of LLM-based tools have been developed for extraction-oriented tasks. However, it's still difficult to find a universal and user-friendly tool for various practical extraction tasks. To address this challenge, we propose OmniExtract, an automatic data extraction tool with user-friendly configuration files that can adapt to various data extraction tasks. OmniExtract employs a prompt optimization method to refine task-specific prompts and achieve high extraction performance. It also supports comprehensive data extraction from both documents and tables, making it applicable to a broad range of data sources. Evaluation results show that OmniExtract obtains a high accuracy ~90% for three datasets. Furthermore, two additional data extraction applications of OmniExtract in real-world scenarios have been presented, achieving an accuracy of 92.21% and ~90% precision and recall, respectively. Specifically, OmniExtract can handle tabular files of various sizes and formats, and achieve over 99% precision and recall on table information extraction tasks. The data reliability performance shows that OmniExtract is a valuable tool for database updating. An online testing service is available at https://ngdc.cncb.ac.cn/omniextract/. The service can be deployed locally with the code in https://github.com/wyb39/OmniExtract.

Large Language Models↗
PubMed1999

B-SPID: an object-relational database architecture to store, retrieve, and manipulate neuroimaging data.

We propose a hardware and software architecture to respond to crucial problems in the neuroimaging field: storage, retrieval, and processing of large datasets. The B-SPID project, here discussed, concerns the processing of neuroimages and attached components stored in an object-relational multimedia database management system (DBMS). Advanced bioinformation concepts are exploited in this project such as large scale data storage, high level graphical user interfaces and 3D graphical processing and display of data. Our database implementation is based on standard programming components, runs on several UNIX platforms and is written to be evolutive. Queries on this database are designed to obtain and display from neuroimaging data several types of results (pictures, text, or 3D graphical shapes) on heterogeneous systems.

Brain Mapping↗
PubMed2006

Managing and mining protein crystallization data.

The crystallization of macromolecules remains a major bottleneck in structural biology. The routine screening of more than one thousand crystallization conditions and subsequent optimization by fine screening presents a challenge to conventional laboratory notebook keeping. In addition, the development of high-throughput robotic crystallization and imaging systems presents a pressing need for low-cost laboratory information management system (LIMS). Here we describe CLIMS2, a crystallization LIMS that features a simple, user-friendly graphical interface, allowing the storage, management, retrieval and mining of crystallization data. The CLIMS2 executable and documentation is freely available at http://clims.med.monash.edu.au.

Computer Graphics↗