65 research outputs found
Medical record: systematic centralization versus secure on demand aggregation
<p>Abstract</p> <p>Background</p> <p>As patients often see the data of their medical histories scattered among various medical records hosted in several health-care establishments, the purpose of our multidisciplinary study was to define a pragmatic and secure on-demand based system able to gather this information, with no risk of breaching confidentiality, and to relay it to a medical professional who asked for the information via a specific search engine.</p> <p>Methods</p> <p>Scattered data are often heterogeneous, which makes the task of gathering information very hard. Two methods can be compared: trying to solve the problem by standardizing and centralizing all the information about every patient in a single Medical Record system or trying to use the data "as is" and find a way to obtain the most complete and the most accurate information. Given the failure of the first approach, due to the lack of standardization or privacy and security problems, for example, we propose an alternative that relies on the current state of affairs: an on-demand system, using a specific search engine that is able to retrieve information from the different medical records of a single patient.</p> <p>Results</p> <p>We describe the function of Medical Record Search Engines (MRSE), which are able to retrieve all the available information regarding a patient who has been hospitalized in different hospitals and to provide this information to health professionals upon request. MRSEs use pseudonymized patient identities and thus never have access to the patient's identity. However, though the system would be easy to implement as it by-passes many of the difficulties associated with a centralized architecture, the health professional would have to validate the information, i.e. read all of the information and create his own synthesis and possibly reject extra data, which could be a drawback. We thus propose various feasible improvements, based on the implementation of several tools in our on-demand based system.</p> <p>Conclusions</p> <p>A system that gathers all of the currently available information regarding a patient on the request of health-care professionals could be of great interest. This low-cost pragmatic alternative to centralized medical records could be developed quickly and easily. It could also be designed to include extra features and should thus be considered by health authorities.</p
Digital image watermarking: its formal model, fundamental properties and possible attacks
While formal definitions and security proofs are well established in some fields like cryptography and steganography, they are not as evident in digital watermarking research. A systematic development of watermarking schemes is desirable, but at present their development is usually informal, ad hoc, and omits the complete realization of application scenarios. This practice not only hinders the choice and use of a suitable scheme for a watermarking application, but also leads to debate about the state-of-the-art for different watermarking applications. With a view to the systematic development of watermarking schemes, we present a formal generic model for digital image watermarking. Considering possible inputs, outputs, and component functions, the initial construction of a basic watermarking model is developed further to incorporate the use of keys. On the basis of our proposed model, fundamental watermarking properties are defined and their importance exemplified for different image applications. We also define a set of possible attacks using our model showing different winning scenarios depending on the adversary capabilities. It is envisaged that with a proper consideration of watermarking properties and adversary actions in different image applications, use of the proposed model would allow a unified treatment of all practically meaningful variants of watermarking schemes
SYMBIOmatics: Synergies in Medical Informatics and Bioinformatics – exploring current scientific literature for emerging topics
Background: The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to http://www.symbiomatics.org). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. Results: This paper presents results ofa systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000-2005 ("recent") and 1990-1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. Conclusion: We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science
Smart Sensors and Virtual Physiology Human Approach as a Basis of Personalized Therapies in Diabetes Mellitus
Diabetes mellitus (DM) has a growing incidence and prevalence in modern societies, pushed by the aging and change of life styles. Despite the huge resources dedicated to improve their quality of life, mortality and morbidity rates, these are still very poor. In this work, DM pathology is revised from clinical and metabolic points of view, as well as mathematical models related to DM, with the aim of justifying an evolution of DM therapies towards the correction of the physiological metabolic loops involved. We analyze the reliability of mathematical models, under the perspective of virtual physiological human (VPH) initiatives, for generating and integrating customized knowledge about patients, which is needed for that evolution. Wearable smart sensors play a key role in this frame, as they provide patient’s information to the models
A first proposal for secure data storage into DNA molecules compliant with biological constraints
International audienceenvisioned in 2025. To respond to associated storage needs, technologies as flash memoryand hard drives reach their limits in terms of: density; energy and ecological costs; durabilityfor long term storage. In this context, data storage on DNA molecules has recently been shownas very promising. DNA storage could be 106 times more dense than hard drives, with alifetime 10 to 20 times longer and an energy consumption closed to zero (molecules can bekept at room temperature with no maintenance).In this work, we are interested in securing archived data. DNA storage being a new technology,the opportunity presents itself to integrate this critical aspect at the biological level, contrarilyto what has been done for electronical storage means. In fact, information must be securedat every step of the DNA data storage chain. Data integrity and confidentiality are among themain issues with threats like data modification (e.g. writing of new data) or the theft of theDNA storage support by an attacker. Herein, we propose a solution for writing encrypted dataonto synthetic DNA molecules considering DNA synthesis and the error-correction codeconstraints. Indeed, DNA sequences should conform to structural constraints dictated by thisbiological process and sequencing
Fast detection and characterization of vessels in very large 3-D data sets using geometrical moments
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