44 research outputs found
Data infrastructures and digital labour : the case of teleradiology
In this thesis, I investigate the effects of digitalisation in teleradiology, the practice of outsourcing radiology diagnosis, through an analysis of the role of infrastructures that enable the transfer, storage, and processing of digital medical data. Consisting of standards, code, protocols and hardware, these infrastructures contribute to the making of complex supply chains that intervene into existing labour processes and produce interdependent relations among radiologists, patients, data engineers, and auxiliary workers. My analysis focuses on three key infrastructures that facilitate teleradiology: Picture Archiving and Communication Systems (PACS), the Digital Imaging and Communication in Medicine (DICOM) standard, and the Health Level 7 (HL7) standard. PACS is a system of four interconnected components: imaging hardware, a secure network, viewing stations for reading images, and data storage facilities. All of these components use DICOM, which specifies data formats and network protocols for the transfer of data within PACS. HL7 is a standard that defines data structures for the purposes of transfer between medical information systems. My research draws on fieldwork in teleradiology companies in Sydney, Australia, and Bangalore, India, which specialise in international outsourcing of medical imaging diagnostics and provide services for hospitals in Europe, USA, and Singapore, among others. I argue that PACS, DICOM, and HL7 establish a technopolitical context that erodes boundaries between social institutions of labour management and material infrastructures of data control. This intertwining of bureaucratic and infrastructural modes of regulation gives rise to a variety of strategies deployed by companies for maximising productivity, as well as counter-strategies of workers in leveraging mobility and qualifications to their advantage
BIOMEDICAL LANGUAGE UNDERSTANDING AND EXTRACTION (BLUE-TEXT): A MINIMAL SYNTACTIC, SEMANTIC METHOD
Clinical text understanding (CTU) is of interest to health informatics because critical clinical information frequently represented as unconstrained text in electronic health records are extensively used by human experts to guide clinical practice, decision making, and to document delivery of care, but are largely unusable by information systems for queries and computations. Recent initiatives advocating for translational research call for generation of technologies that can integrate structured clinical data with unstructured data, provide a unified interface to all data, and contextualize clinical information for reuse in multidisciplinary and collaborative environment envisioned by CTSA program. This implies that technologies for the processing and interpretation of clinical text should be evaluated not only in terms of their validity and reliability in their intended environment, but also in light of their interoperability, and ability to support information integration and contextualization in a distributed and dynamic environment.
This vision adds a new layer of information representation requirements that needs to be accounted for when conceptualizing implementation or acquisition of clinical text processing tools and technologies for multidisciplinary research.
On the other hand, electronic health records frequently contain unconstrained clinical text with high variability in use of terms and documentation practices, and without commitmentto grammatical or syntactic structure of the language (e.g. Triage notes, physician and nurse notes, chief complaints, etc). This hinders performance of natural language processing technologies which typically rely heavily on the syntax of language and grammatical structure of the text.
This document introduces our method to transform unconstrained clinical text found in electronic health information systems to a formal (computationally understandable) representation that is suitable for querying, integration, contextualization and reuse, and is resilient to the grammatical and syntactic irregularities of the clinical text. We present our design rationale, method, and results of evaluation in processing chief complaints and triage notes from 8 different emergency departments in Houston Texas. At the end, we will discuss significance of our contribution in enabling use of clinical text in a practical bio-surveillance setting
Pacific Symposium on Biocomputing 2023
The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field
Cell-Free Nucleic Acids
The deficits of mammography and the potential of noninvasive diagnostic testing using circulating miRNA profiles are presented in our first review article. Exosomes are important in the transfer of genetic information. The current knowledge on exosome-associated DNAs and on vesicle-associated DNAs and their role in pregnancy-related complications is presented in the next article. The major obstacle is the lack of a standardized technique for the isolation and measurement of exosomes. One review has summarized the latest results on cell-free nucleic acids in inflammatory bowel disease (IBD). Despite the extensive research, the etiology and exact pathogenesis are still unclear, although similarity to the cell-free ribonucleic acids (cfRNAs) observed in other autoimmune diseases seems to be relevant in IBD. Liquid biopsy is a useful tool for the differentiation of leiomyomas and sarcomas in the corpus uteri. One manuscript has collected the most important knowledge of mesenchymal uterine tumors and shows the benefits of noninvasive sampling. Microchimerism has also recently become a hot topic. It is discussed in the context of various forms of transplantation and transplantation-related advanced therapies, the available cell-free nucleic acid (cfNA) markers, and the detection platforms that have been introduced. Ovarian cancer is one of the leading serious malignancies among women, with a high incidence of mortality; the introduction of new noninvasive diagnostic markers could help in its early detection and treatment monitoring. Epigenetic regulation is very important during the development of diseases and drug resistance. Methylation changes are important signs during ovarian cancer development, and it seems that the CDH1 gene is a potential candidate for being a noninvasive biomarker in the diagnosis of ovarian cancer. Preeclampsia is a mysterious disease—despite intensive research, the exact details of its development are unknown. It seems that cell-free nucleic acids could serve as biomarkers for the early detection of this disease. Three research papers deal with the prenatal application of cfDNA. Copy number variants (CNVs) are important subjects for the study of human genome variations, as CNVs can contribute to population diversity and human genetic diseases. These are useful in NIPT as a source of population specific data. The reliability of NIPT depends on the accurate estimation of fetal fraction. Improvement in the success rate of in vitro fertilization (IVF) and embryo transfer (ET) is an important goal. The measurement of embryo-specific small noncoding RNAs in culture media could improve the efficiency of ET
Combining SOA and BPM Technologies for Cross-System Process Automation
This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation
Development of new knowledge discovery tools to explore biomedical datasets in breast cancer
The explorative power of high throughput technologies in cancer research has become well established in recent years, exemplified by diverse gene microarray studies. However, development of the necessary biomedical data analysis tools has historically been confined to a commercial environment, while comprehensive, user-friendly analysis approaches are still needed. Availability of freely-available software, notably the 'R' project statistical programming language, allowed development of a user-friendly multivariate statistics application - Informatics Tenovus (I-10) - in this project. I-10 provides a platform through which powerful existing and future 'R' project statistical analysis methodologies can be applied, without prior programming knowledge. The new system was tested in the context of exploring antihormone resistance in breast cancer, analysing microarray datasets from in vitro models of acquired Tamoxifen (TAMR) or Faslodex resistance (FASR) versus endocrine responsive MCF-7 cells. The analysis not only revealed known de-regulated genes, but also further potential future markers/targets for endocrine response/resistance. The advantages of the 'R' programming environment together with Microsoft Visual Basic.net technology for producing user-friendly biomedical analysis tools facilitated subsequent development of a tool which could explore SEER cancer patient datasets. This new cancer query survival tool - Superstes -allows detailed statistical modelling of the impact that multiple patient attributes (in this instance derived from the SEER breast and colorectal cancer datasets) have on patient survival. The versatility of 'R' was additionally demonstrated in further exploring classifiers, where it was able to interface with the sophisticated, freely available machine learning application 'Weka'. Using 'R' and Weka, breast cancer patient survival was modelled using equivalent patient attributes to the Nottingham Prognostic Index and a 10 year survival subset of the SEER breast cancer dataset. Several machine learning methodologies were compared for their ability to accurately model survival, with their value in routine clinical use for prediction of patient survival then critically evaluated.EThOS - Electronic Theses Online ServiceGBUnited Kingdo