Implementation of medical imaging with telemedicine for the early detection and diagnoses of breast cancer to women in remote areas

Nowadays, the cancer topic has become a global concern. Furthermore, breast cancer persists to be the top leading cause of death to women population and the second cause of cancer death after the lung cancer globally. Various technologies and techniques have been searched, developed and studied over the years to detect the disease at the early stage; the early diagnosis saves many lives in both developed and developing countries. The detection of cancer through a screening process before its symptoms emerge increases the survival rate dramatically (Li, Meaney and Paulsen). Moreover, sufficient knowledge of the disease, qualified staff, accurate, appropriate treatment and diagnosis contribute to the successful cure of the disease; however, the cancer treatment is not affordable by many and sometimes not available to the very needy, and more precisely in developing countries. In this research, we aimed to explore the early detection of breast cancer using the new image compression algorithm: DYNAMAC, a compression tool that finds its basis in nonlinear dynamical systems theory; we implemented this algorithm through the D-transform, a digital sequence used to compress the digital media (Wang and Huang) & (Antoine, Murenzi and Vandergheynst). The goal is to use this method to analyze the average profile of diseased and healthy breast images obtained from a digital mammography to detect diseased tissues. After the detection of cancerous tumors, we worked to establish a remote care to women victims of breast cancer using the Telecommunication infrastructure through primarily Teleradiology and the Next Generation Internet (NGI) technology. Over the methods and techniques previously used in the area of medical imaging techniques, DYNAMAC algorithm is the most easily implemented along with its features that include cost saving in addition to best meeting the requirements of the breast imaging technology

Designing a secure ubiquitous mammography consultation system

This thesis attempts to design and develop a prototype for mammography image consultation that can work securely within a ubiquitous environment. Mammogram images differ largely from other type of images and it requires special and dedicated techniques to identify the required regions of interest. Thus in Chapter 2 we started to explore the affectivity of the various traditional techniques based on convolution operators (e.g. Sobol, Pretwitt, Canny) for mammography edge detection. The second part of chapter 2 tries to enhance the results obtained via the traditional techniques by hybriding some of them. The hybriding technique is called in our thesis as Pipelined Operators. In this direction we proposed four pipeline operators, which contribute to the edge enhancement as well as abnormalities rendering through the introduction of an additional coloring mechanism. Although the visualization pipelines represent in our view an advancement on the traditional techniques applied to mammograms, such pipelines expose healthcare users to further usage complexities. For this purpose we extended our research work in chapter 2 to find a better single technique that can work smoothly within the healthcare system. In this direction, we developed in the third part of chapter 2 a novel technique for finding edges based on analyzing the dynamic and fuzzy nature of edges in mammograms. We called our developed method as "Dynamic Fuzzy Classifier or the DFC"

Decentralized Telemedicine Framework for a Smart Healthcare Ecosystem

The healthcare sector is one of the most rapidly growing sectors globally. With the ever-growing technology, patient care, regulatory compliance, and digital transformation, there is an increased need for healthcare sectors to collaborate with all stakeholders – both within the healthcare ecosystem and in concurring industries. In recent times, telemedicine has proven to provide high quality, affordable, and predominantly adapted healthcare services. However, telemedicine suffers from several risks in implementation, such as data breach, restricted access across medical fraternity, incorrect diagnosis and prescription, fraud, and abuse. In this work, introduce blockchain-based framework that would unlock the future of the healthcare sector and improved services. Our proposed solution utilizing Ethereum smart contracts to develop a transparent, tamper-proof telemedicine healthcare framework, and ensure the integrity of sensitive patient data eliminating a central administrator. Moreover, the smart contract regulates the interaction between all the parties involved in the network and keeps the patient meticulously informed about the transactions in the network

Grid-based semantic integration of heterogeneous data resources: Implementation on a HealthGrid

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.The semantic integration of geographically distributed and heterogeneous data resources still remains a key challenge in Grid infrastructures. Today's mainstream Grid technologies hold the promise to meet this challenge in a systematic manner, making data applications more scalable and manageable. The thesis conducts a thorough investigation of the problem, the state of the art, and the related technologies, and proposes an Architecture for Semantic Integration of Data Sources (ASIDS) addressing the semantic heterogeneity issue. It defines a simple mechanism for the interoperability of heterogeneous data sources in order to extract or discover information regardless of their different semantics. The constituent technologies of this architecture include Globus Toolkit (GT4) and OGSA-DAI (Open Grid Service Architecture Data Integration and Access) alongside other web services technologies such as XML (Extensive Markup Language). To show this, the ASIDS architecture was implemented and tested in a realistic setting by building an exemplar application prototype on a HealthGrid (pilot implementation). The study followed an empirical research methodology and was informed by extensive literature surveys and a critical analysis of the relevant technologies and their synergies. The two literature reviews, together with the analysis of the technology background, have provided a good overview of the current Grid and HealthGrid landscape, produced some valuable taxonomies, explored new paths by integrating technologies, and more importantly illuminated the problem and guided the research process towards a promising solution. Yet the primary contribution of this research is an approach that uses contemporary Grid technologies for integrating heterogeneous data resources that have semantically different. data fields (attributes). It has been practically demonstrated (using a prototype HealthGrid) that discovery in semantically integrated distributed data sources can be feasible by using mainstream Grid technologies, which have been shown to have some Significant advantages over non-Grid based approaches

3rd EGEE User Forum

We have organized this book in a sequence of chapters, each chapter associated with an application or technical theme introduced by an overview of the contents, and a summary of the main conclusions coming from the Forum for the chapter topic. The first chapter gathers all the plenary session keynote addresses, and following this there is a sequence of chapters covering the application flavoured sessions. These are followed by chapters with the flavour of Computer Science and Grid Technology. The final chapter covers the important number of practical demonstrations and posters exhibited at the Forum. Much of the work presented has a direct link to specific areas of Science, and so we have created a Science Index, presented below. In addition, at the end of this book, we provide a complete list of the institutes and countries involved in the User Forum

Grid-based semantic integration of heterogeneous data resources : implementation on a HealthGrid

The semantic integration of geographically distributed and heterogeneous data resources still remains a key challenge in Grid infrastructures. Today's mainstream Grid technologies hold the promise to meet this challenge in a systematic manner, making data applications more scalable and manageable. The thesis conducts a thorough investigation of the problem, the state of the art, and the related technologies, and proposes an Architecture for Semantic Integration of Data Sources (ASIDS) addressing the semantic heterogeneity issue. It defines a simple mechanism for the interoperability of heterogeneous data sources in order to extract or discover information regardless of their different semantics. The constituent technologies of this architecture include Globus Toolkit (GT4) and OGSA-DAI (Open Grid Service Architecture Data Integration and Access) alongside other web services technologies such as XML (Extensive Markup Language). To show this, the ASIDS architecture was implemented and tested in a realistic setting by building an exemplar application prototype on a HealthGrid (pilot implementation). The study followed an empirical research methodology and was informed by extensive literature surveys and a critical analysis of the relevant technologies and their synergies. The two literature reviews, together with the analysis of the technology background, have provided a good overview of the current Grid and HealthGrid landscape, produced some valuable taxonomies, explored new paths by integrating technologies, and more importantly illuminated the problem and guided the research process towards a promising solution. Yet the primary contribution of this research is an approach that uses contemporary Grid technologies for integrating heterogeneous data resources that have semantically different. data fields (attributes). It has been practically demonstrated (using a prototype HealthGrid) that discovery in semantically integrated distributed data sources can be feasible by using mainstream Grid technologies, which have been shown to have some Significant advantages over non-Grid based approaches.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Moving Research Into Practice: The Diffusion of Evidence-Based Recommendations Through Professional Societies

INTRODUCTION There is a substantial need among clinicians for health-related, evidence-based recommendations. Evidence-based recommendations help distill research findings and aid health care providers in making clinical decisions. However, it is infeasible for providers to sort through thousands of available guidelines, and heterogeneity among recommendation developers (e.g., composition, processes, outputs) can make it difficult for clinicians to identify which recommendations are trustworthy, feasible, and applicable to their patient population. Even when there is broad consensus about the quality and utility of recommendations, a range of contextual factors (e.g., the health care system, patient characteristics, enabling resources) can impede implementation. This study examined the diffusion of evidence-based recommendations through professional societies to clinically-trained members, and explored knowledge, attitudes, beliefs, and behaviors regarding evidence-based recommendations and practice. The study had three aims: 1) Describe the role primary care professional societies play in developing and/or disseminating evidence-based reports and recommendations. 2) Determine if the needs of primary care providers and their professional societies for evidence-based reports and recommendations are being met. 3) Describe the value that the federal government contributes to evidence-based practice. METHODS To achieve these aims, content analysis was used to examine transcripts from 34 semi-structured telephone interviews of leaders and members from eight health-related professional societies. Nonprobability, purposive sampling of knowledgeable experts enabled in-depth exploration of phenomena. An interview guide was developed using theory-driven concepts and theoretical frameworks, and was pilot tested using cognitive interviewing techniques. The codebook included theory-and data-driven codes and was revised through an iterative process that included intercoder reliability assessments. RESULTS There were differing views on the meaning of “evidence-based”, but there was broad agreement on its scientific underpinning and the importance of conducting “evidence-based practice.” Professional societies can play several roles (i.e., disseminator, liaison, developer, and/or facilitator) in the promotion of evidence-based recommendations and practice. Views varied on whether the needs of primary care providers and their professional societies for evidence-based reports and recommendations were being met. Federally-sponsored recommendation developers were viewed as valuable contributors to evidence-based practice because of their objectivity, transparency, balance, methodological rigor, and prioritization. Study participants offered many suggestions for improving the development, feasibility, readability, acceptability, and dissemination of evidence-based recommendations. Participants also offered input on how federally-sponsored recommendation developers could strengthen their partnerships with stakeholders, including professional societies and their members. CONCLUSION The issue of trust was central to participants’ attitudes and beliefs; therefore, recommendation developers should integrate transparency and three factors that bolster trust (ability, benevolence, and integrity) into their processes. Federally-sponsored recommendation developers should consider collaborating with professional societies in a variety of ways to develop and disseminate recommendations to facilitate evidence-based practice. The federal government can also promote the use of evidence-based recommendations by improving its guideline clearinghouse, expanding health insurance coverage to more Americans, requiring that recommendations be covered by insurance, and supporting research on point-of-care decision support tools, electronic health records, and workflow training for health providers

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering