A window-based time series feature extraction method.

This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets.

A novel approach to optimize workflow in grid-based teleradiology applications.

BACKGROUND AND OBJECTIVE: This study proposes an infrastructure with a reporting workflow optimization algorithm (RWOA) in order to interconnect facilities, reporting units and radiologists on a single access interface, to increase the efficiency of the reporting process by decreasing the medical report turnaround time and to increase the quality of medical reports by determining the optimum match between the inspection and radiologist in terms of subspecialty, workload and response time. METHODS: Workflow centric network architecture with an enhanced caching, querying and retrieving mechanism is implemented by seamlessly integrating Grid Agent and Grid Manager to conventional digital radiology systems. The inspection and radiologist attributes are modelled using a hierarchical ontology structure. Attribute preferences rated by radiologists and technical experts are formed into reciprocal matrixes and weights for entities are calculated utilizing Analytic Hierarchy Process (AHP). The assignment alternatives are processed by relation-based semantic matching (RBSM) and Integer Linear Programming (ILP). RESULTS: The results are evaluated based on both real case applications and simulated process data in terms of subspecialty, response time and workload success rates. Results obtained using simulated data are compared with the outcomes obtained by applying Round Robin, Shortest Queue and Random distribution policies. The proposed algorithm is also applied to a real case teleradiology application process data where medical reporting workflow was performed based on manual assignments by the chief radiologist for 6225 inspections. CONCLUSIONS: RBSM gives the highest subspecialty success rate and integrating ILP with RBSM ratings as RWOA provides a better response time and workload distribution success rate. RWOA based image delivery also prevents bandwidth, storage or hardware related stuck and latencies. When compared with a real case teleradiology application where inspection assignments were performed manually, the proposed solution was found to increase the experience success rate by 13.25%, workload success rate by 63.76% and response time success rate by 120%. The total response time in the real case application data was improved by 22.39%.

Policymaking to preserve privacy in disclosure of public health data: a suggested framework.

Health organisations in Turkey gather a vast amount of valuable individual data that can be used for public health purposes. The organisations use rigid methods to remove some useful details from the data while publishing the rest of the data in a highly aggregated form, mostly because of privacy concerns and lack of standardised policies. This action leads to information loss and bias affecting public health research. Hence, organisations need dynamic policies and well-defined procedures rather than a specific algorithm to protect the privacy of individual data. To address this need, we developed a framework for the systematic application of anonymity methods while reducing and objectively reporting the information loss without leaking confidentiality. This framework acts as a roadmap for policymaking by providing high-level pseudo-policies with semitechnical guidelines in addition to some sample scenarios suitable for policymakers, public health programme managers and legislators.

Integration of federated medical systems for vendor neutral image access in teleradiology applications.

This paper proposes a framework designed to interconnect medical imaging facilities and teleradiology service providers on a single access interface. This framework aims to solve the interoperability issues of Picture Archiving and Communication System (PACS), Radiology Information System (RIS) and Hospital Information System (HIS) developed by different vendors and enrich the digital health record delivered to non-local radiologists or physicians with the integrated information from several systems. This is achieved by introducing a "Grid Agent" into the domain of medical software systems, which seamlessly integrates with present systems and forms a network to deliver data between other Grid Agents and the "Grid Manager". Resultant solution decreases the access time of medical images by non-local medical staff and increases the efficiency and durability of the teleradiology service architecture.

A knowledge based search tool for performance measures in health care systems.

Performance measurement is vital for improving the health care systems. However, we are still far from having accepted performance measurement models. Researchers and developers are seeking comparable performance indicators. We developed an intelligent search tool to identify appropriate measures for specific requirements by matching diverse care settings. We reviewed the literature and analyzed 229 performance measurement studies published after 2000. These studies are evaluated with an original theoretical framework and stored in the database. A semantic network is designed for representing domain knowledge and supporting reasoning. We have applied knowledge based decision support techniques to cope with uncertainty problems. As a result we designed a tool which simplifies the performance indicator search process and provides most relevant indicators by employing knowledge based systems.

Design and evaluation of an ontology based information extraction system for radiological reports.

This paper describes an information extraction system that extracts and converts the available information in free text Turkish radiology reports into a structured information model using manually created extraction rules and domain ontology. The ontology provides flexibility in the design of extraction rules, and determines the information model for the extracted semantic information. Although our information extraction system mainly concentrates on abdominal radiology reports, the system can be used in another field of medicine by adapting its ontology and extraction rule set. We achieved very high precision and recall results during the evaluation of the developed system with unseen radiology reports.

An integrated approach to breast diseases and breast cancer registry and research: BDRS as a web-based multi-institutional model.

Accurate, complete, and timely health data sources are essential for progress in health care. Registry and research systems are foundations for conducting clinical and epidemiological research. Developing countries lack these systems due to the scarcity of the resources allocated for health information systems. In this study, we provide an integrated model for Turkey in order to optimize the utilization of resources. The Breast Diseases Registry system (BDRS) is implemented as an integrated disease-specific system for breast diseases in order to obtain a comprehensive use of patient health data for research and Breast Cancer Registry as well as an ancillary clinical tool.

MedicoPort: a medical search engine for all.

We present a new next generation domain search engine called MedicoPort. MedicoPort is a medical search engine designed for the users with no medical expertise. It is enhanced with the domain knowledge obtained from Unified Medical Language System (UMLS) to increase the effectiveness of the searches. The power of the system is based on the ability to understand the semantics of web pages and the user queries. MedicoPort transforms a keyword search into a conceptual search. Through our system we present a topical web crawling technique and indexing techniques empowered by the semantics information. MedicoPort aims to generate maximum output with semantic value using minimum input from the user. Since MedicoPort is designed to help people seeking information about health on the web, our target users are not medical specialists who can effectively use the special jargon of medicine and access medical databases. Medical experts have the advantage of shrinking the answer set by expressing several terms using medical terminology. MedicoPort provides the same advantage to its users through the automated use of the medical domain knowledge in the background. The results of our experiments indicate that, expanding the queries with domain knowledge, such as using the synonyms and partially or contextually relevant terms from UMLS, increase dramatically the relevance of an answer set produced by MedicoPort and the number of retrieved web pages that are relevant to the user request.

EVEREST: an efficient method for verification of digital signatures in real-time teleradiology.

The introduction of digital medical images requires a legally binding digital signature that guarantees authenticity and integrity of the image. In real-time teleradiology services, the system is expected to respond very quickly however to verify the signature a considerable amount of time is spent to compute the hash value of the image since the image size might be huge (tens of megabytes). Motivating by this fact, in this paper we propose EVEREST, an efficient methodology for verification. The key observation we have made is that in the traditional verification the processor of the verifying machine is idle (I/O blocked) while the image is downloaded. In EVEREST, to improve the real-time efficiency the receiver can perform most of the hash computation while he is receiving the image itself. One other important advantage of our scheme is the communication efficiency since getting the entire image file is no longer necessary to detect the tampering.

Survivable authentication for health information systems.

Possible solutions to establish a survivable authentication framework in a health information system including the one based on one-time passwords (OTPs) are discussed. A new convenient method to generate OTPs is proposed.

Integrated breast diseases research and cancer registry in Turkey.

A system we call BDRS is implemented as an integrated disease specific system for breast diseases in order to obtain and use patient health data for clinical research, cancer registry and clinical care. It is an open, flexible and modular system that supports multi-institutional and multi-viewed utilization of health data. Three-tier web based architecture, and object oriented technologies have been employed to ensure its extendibility. Exchange and sharing of health data have been implemented with XML.