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Systems thinking for health systems strengthening
Many developing countries are looking to scale-up what works through major systems strengthening investments. With leadership, conviction and commitment, systems thinking can facilitate and accelerate the strengthening of systems to more effectively deliver interventions to those in need and be better able to improve health in an equitable way. Systems thinking is not a panacea. Its application does not mean that resolving problems and weaknesses will come easily or naturally or without overcoming the inertia of the established way of doing things. But it will identify, with more precision, where some of the true blockages and challenges lie. It will help to: 1) explore these problems from a systems perspective; 2) show potentials of solutions that work across sub-systems; 3) promote dynamic networks of diverse stakeholders; 4) inspire learning; and 5) foster more system-wide planning, evaluation and research. And it will increase the likelihood that health system strengthening investments and interventions will be effective. The more often and more comprehensively the actors and components of the system can talk to each other from within a common framework --communicating, sharing, problem-solving - the better chance any initiative to strengthen health systems has. Real progress will undoubtedly require time, significant change, and momentum to build capacity across the system. However, the change is necessary - and needed now. This report therefore speaks to health system stewards, researchers and funders and maps out a set of strategies and activities to harness these approaches, to link them to these emerging opportunities and to assist systems thinking to become the norm in design and evaluation of interventions in health systems. But, the final message is to the funders of health system strengthening and health systems research who will
need to recognize the potential in these opportunities, be prepared to take risks in investing in such innovations, and play an active role in both driving and following this agenda towards more systemic and evidence-informed health development.
eBook
Artificial intelligence and machine learning in 2D/3D medical image processing
\"Medical image fusion is a process which merges information from multiple images of the same scene. The fused image provides appended information that can be utilized for more precise localization of abnormalities. The use of medical image processing databases will help to create and develop more accurate and diagnostic tools\"-- Provided by publisher.
Book
Handbook of evaluation methods for health informatics
This Handbook provides a complete compendium of methods for evaluation of IT-based systems and solutions within healthcare. Emphasis is entirely on assessment of the IT-system within its organizational environment. The author provides a coherent and complete assessment of methods addressing interactions with and effects of technology at the organizational, psychological, and social levels.It offers an explanation of the terminology and theoretical foundations underlying the methodological analysis presented here. The author carefully guides the reader through the process of identifying relevant methods corresponding to specific information needs and conditions for carrying out the evaluation study. The Handbook takes a critical view by focusing on assumptions for application, tacit built-in perspectives of the methods as well as their perils and pitfalls. *Collects a number of evaluation methods of medical informatics*Addresses metrics and measures*Includes an extensive list of anotated references, case studies, and a list of useful Web sites
eBook
Multiomics Analysis Reveals the Impact of Microbiota on Host Metabolism in Hepatic Steatosis
Metabolic dysfunction‐associated fatty liver disease (MAFLD) is a complex disease involving alterations in multiple biological processes regulated by the interactions between obesity, genetic background, and environmental factors including the microbiome. To decipher hepatic steatosis (HS) pathogenesis by excluding critical confounding factors including genetic variants and diabetes, 56 heterogenous MAFLD patients are characterized by generating multiomics data including oral and gut metagenomics as well as plasma metabolomics and inflammatory proteomics data. The dysbiosis in the oral and gut microbiome is explored and the host–microbiome interactions based on global metabolic and inflammatory processes are revealed. These multiomics data are integrated using the biological network and HS's key features are identified using multiomics data. HS is finally predicted using these key features and findings are validated in a follow‐up cohort, where 22 subjects with varying degree of HS are characterized. A comprehensive study to decipher hepatic steatosis (HS) by generating multiomics data including oral and gut metagenomics as well as plasma metabolomics and inflammatory proteomics data in a well‐characterized metabolic dysfunction‐associated fatty liver disease (MAFLD) cohort.
Journal Article
Engineering Systems Integration
The first book to address the underlying premises of systems integration and how to exposit them into a practical and productive manner, this book prepares systems managers and systems engineers to consider their decisions in light of systems integration metrics. The book addresses two questions: Is there a way to express the interplay of human actions and the result of system interactions of a product with its environment, and are there methods that combine to improve the integration of systems? The systems integration theory and integration frameworks proposed in the book tie General Systems Theory with practice.
eBook
Image processing and intelligent computing systems
\"There is a drastic growth in multimedia data. Even during the Covid-19 pandemic, we observed that the images helped doctors immensely in fast detection of Covid-19 infection in patients. There are many critical applications where images play a vital role. These applications use raw image data to extract some useful information about the world around us. Quick extraction of valuable information from raw images is one challenge that academicians and professionals face nowadays. This is where image processing comes into action. Image processing's primary purpose is to get an enhanced image or extract some useful information from it. Therefore, there is a major need for some technique or system that addresses this challenge. Intelligent Systems have emerged as a solution to address quick image information extraction. In simple words, an Intelligent System can be defined as a mathematical model that adapts itself to deal with the problems' dynamicity. These systems learn how to act so it can reach their objectives. Intelligent System helps accomplish various image processing functions like enhancement, segmentation, reconstruction, object detection, and morphing. The advent of Intelligent Systems in the image processing field has leveraged many critical applications for humankind. These critical applications include factory automation, biomedical imaging analysis, and decision-econometrics, Intelligent Systems and challenges\"-- Provided by publisher.
Book
Handbook of Healthcare Delivery Systems
While system engineering concepts have been broadly applied in healthcare systems, most improvements have focused on a specific segment or unit of the delivery system. Using a system engineering perspective, this handbook offers theoretical foundations, methodologies, and case studies in each main sector of the system. It explores how system engineering methodologies and their applications could improve patient outcomes and cost effectiveness and offers a comprehensive description of the healthcare delivery system from the macro level (hospitals) to the micro level (operating room).
eBook