Data Driven Science For Clinically Actionable Knowledge In Diseases
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Data Driven Science For Clinically Actionable Knowledge In Diseases
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Author : Daniel R. Catchpoole
language : en
Publisher: CRC Press
Release Date : 2023-12-06
Data Driven Science For Clinically Actionable Knowledge In Diseases written by Daniel R. Catchpoole and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-06 with Medical categories.
Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods, meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory, method, models, design, evaluation and applications in computational and visual analytics in desktop, mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis, including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain, the book demonstrates how analytics influences the domain through improving decision making, specifying diagnostics, selecting the best treatments and generating clinical certainty.
Data Driven Science For Clinically Actionable Knowledge In Diseases
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Author : Daniel R. Catchpoole
language : en
Publisher:
Release Date : 2023
Data Driven Science For Clinically Actionable Knowledge In Diseases written by Daniel R. Catchpoole and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Diseases categories.
Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods, meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory, method, models, design, evaluation and applications in computational and visual analytics in desktop, mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis, including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain, the book demonstrates how analytics influences the domain through improving decision making, specifying diagnostics, selecting the best treatments and generating clinical certainty.
Data Driven Science For Clinically Actionable Knowledge In Diseases
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Author : Daniel Catchpoole
language : en
Publisher: CRC Press
Release Date : 2023-12-06
Data Driven Science For Clinically Actionable Knowledge In Diseases written by Daniel Catchpoole and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-06 with Medical categories.
Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods, meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory, method, models, design, evaluation and applications in computational and visual analytics in desktop, mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis, including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain, the book demonstrates how analytics influences the domain through improving decision making, specifying diagnostics, selecting the best treatments and generating clinical certainty.
Handbook Of Research On Ai Methods And Applications In Computer Engineering
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Author : Kaddoura, Sanaa
language : en
Publisher: IGI Global
Release Date : 2023-01-30
Handbook Of Research On Ai Methods And Applications In Computer Engineering written by Kaddoura, Sanaa and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-30 with Computers categories.
The development of artificial intelligence (AI) involves the creation of computer systems that can do activities that would ordinarily require human intelligence, such as visual perception, speech recognition, decision making, and language translation. Through increasingly complex programming approaches, it has been transforming and advancing the discipline of computer science. The Handbook of Research on AI Methods and Applications in Computer Engineering illuminates how todays computer engineers and scientists can use AI in real-world applications. It focuses on a few current and emergent AI applications, allowing a more in-depth discussion of each topic. Covering topics such as biomedical research applications, navigation systems, and search engines, this premier reference source is an excellent resource for computer scientists, computer engineers, IT managers, students and educators of higher education, librarians, researchers, and academicians.
Data Science And Predictive Analytics
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Author : Ivo D. Dinov
language : en
Publisher: Springer
Release Date : 2019-01-25
Data Science And Predictive Analytics written by Ivo D. Dinov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-25 with Computers categories.
Over the past decade, Big Data have become ubiquitous in all economic sectors, scientific disciplines, and human activities. They have led to striking technological advances, affecting all human experiences. Our ability to manage, understand, interrogate, and interpret such extremely large, multisource, heterogeneous, incomplete, multiscale, and incongruent data has not kept pace with the rapid increase of the volume, complexity and proliferation of the deluge of digital information. There are three reasons for this shortfall. First, the volume of data is increasing much faster than the corresponding rise of our computational processing power (Kryder’s law > Moore’s law). Second, traditional discipline-bounds inhibit expeditious progress. Third, our education and training activities have fallen behind the accelerated trend of scientific, information, and communication advances. There are very few rigorous instructional resources, interactive learning materials, and dynamic training environments that support active data science learning. The textbook balances the mathematical foundations with dexterous demonstrations and examples of data, tools, modules and workflows that serve as pillars for the urgently needed bridge to close that supply and demand predictive analytic skills gap. Exposing the enormous opportunities presented by the tsunami of Big data, this textbook aims to identify specific knowledge gaps, educational barriers, and workforce readiness deficiencies. Specifically, it focuses on the development of a transdisciplinary curriculum integrating modern computational methods, advanced data science techniques, innovative biomedical applications, and impactful health analytics. The content of this graduate-level textbook fills a substantial gap in integrating modern engineering concepts, computational algorithms, mathematical optimization, statistical computing and biomedical inference. Big data analytic techniques and predictive scientific methods demand broad transdisciplinary knowledge, appeal to an extremely wide spectrum of readers/learners, and provide incredible opportunities for engagement throughout the academy, industry, regulatory and funding agencies. The two examples below demonstrate the powerful need for scientific knowledge, computational abilities, interdisciplinary expertise, and modern technologies necessary to achieve desired outcomes (improving human health and optimizing future return on investment). This can only be achieved by appropriately trained teams of researchers who can develop robust decision support systems using modern techniques and effective end-to-end protocols, like the ones described in this textbook. • A geriatric neurologist is examining a patient complaining of gait imbalance and posture instability. To determine if the patient may suffer from Parkinson’s disease, the physician acquires clinical, cognitive, phenotypic, imaging, and genetics data (Big Data). Most clinics and healthcare centers are not equipped with skilled data analytic teams that can wrangle, harmonize and interpret such complex datasets. A learner that completes a course of study using this textbook will have the competency and ability to manage the data, generate a protocol for deriving biomarkers, and provide an actionable decision support system. The results of this protocol will help the physician understand the entire patient dataset and assist in making a holistic evidence-based, data-driven, clinical diagnosis. • To improve the return on investment for their shareholders, a healthcare manufacturer needs to forecast the demand for their product subject to environmental, demographic, economic, and bio-social sentiment data (Big Data). The organization’s data-analytics team is tasked with developing a protocol that identifies, aggregates, harmonizes, models and analyzes these heterogeneous data elements to generate a trend forecast. This system needs to provide an automated, adaptive, scalable, and reliable prediction of the optimal investment, e.g., R&D allocation, that maximizes the company’s bottom line. A reader that complete a course of study using this textbook will be able to ingest the observed structured and unstructured data, mathematically represent the data as a computable object, apply appropriate model-based and model-free prediction techniques. The results of these techniques may be used to forecast the expected relation between the company’s investment, product supply, general demand of healthcare (providers and patients), and estimate the return on initial investments.
Data Science In Critical Care An Issue Of Critical Care Clinics E Book
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Author : Rishikesan Kamaleswaran
language : en
Publisher: Elsevier Health Sciences
Release Date : 2023-09-13
Data Science In Critical Care An Issue Of Critical Care Clinics E Book written by Rishikesan Kamaleswaran and has been published by Elsevier Health Sciences this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-13 with Medical categories.
In this issue of Critical Care Clinics, guest editors Drs. Rishikesan Kamaleswaran and Andre L. Holder bring their considerable expertise to the topic of Data Science in Critical Care. Data science, the field of study dedicated to the principled extraction of knowledge from complex data, is particularly relevant in the critical care setting. In this issue, top experts in the field cover key topics such as refining our understanding and classification of critical illness using biomarker-based phenotyping; predictive modeling using AI/ML on EHR data; classification and prediction using waveform-based data; creating trustworthy and fair AI systems; and more. Contains 15 relevant, practice-oriented topics including AI and the imaging revolution; designing “living, breathing clinical trials: lessons learned from the COVID-19 pandemic; the patient or the population: knowing the limitations of our data to make smart clinical decisions; weighing the cost vs. benefit of AI in healthcare; and more. Provides in-depth clinical reviews on data science in critical care, offering actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.
Translational Systems Biology
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Author : Yoram Vodovotz
language : en
Publisher: Elsevier
Release Date : 2014-10-08
Translational Systems Biology written by Yoram Vodovotz and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-08 with Technology & Engineering categories.
Are we satisfied with the rate of drug development? Are we happy with the drugs that come to market? Are we getting our money’s worth in spending for basic biomedical research? In Translational Systems Biology, Drs. Yoram Vodovotz and Gary An address these questions by providing a foundational description the barriers facing biomedical research today and the immediate future, and how these barriers could be overcome through the adoption of a robust and scalable approach that will form the underpinning of biomedical research for the future. By using a combination of essays providing the intellectual basis of the Translational Dilemma and reports of examples in the study of inflammation, the content of Translational Systems Biology will remain relevant as technology and knowledge advances bring broad translational applicability to other diseases. Translational systems biology is an integrated, multi-scale, evidence-based approach that combines laboratory, clinical and computational methods with an explicit goal of developing effective means of control of biological processes for improving human health and rapid clinical application. This comprehensive approach to date has been utilized for in silico studies of sepsis, trauma, hemorrhage, and traumatic brain injury, acute liver failure, wound healing, and inflammation. Provides an explicit, reasoned, and systematic approach to dealing with the challenges of translational science across disciplines Establishes the case for including computational modeling at all stages of biomedical research and healthcare delivery, from early pre-clinical studies to long-term care, by clearly delineating efficiency and costs saving important to business investment Guides readers on how to communicate across domains and disciplines, particularly between biologists and computational researchers, to effectively develop multi- and trans-disciplinary research teams
Data Science In Critical Care An Issue Of Critical Care Clinics Volume 39 4
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Author : Rishikesan Kamaleswaran
language : en
Publisher: Clinics: Internal Medicine
Release Date : 2023-09-14
Data Science In Critical Care An Issue Of Critical Care Clinics Volume 39 4 written by Rishikesan Kamaleswaran and has been published by Clinics: Internal Medicine this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-14 with Medical categories.
In this issue of Critical Care Clinics, guest editors Drs. Rishikesan Kamaleswaran and Andre L. Holder bring their considerable expertise to the topic of Data Science in Critical Care. Data science, the field of study dedicated to the principled extraction of knowledge from complex data, is particularly relevant in the critical care setting. In this issue, top experts in the field cover key topics such as refining our understanding and classification of critical illness using biomarker-based phenotyping; predictive modeling using AI/ML on EHR data; classification and prediction using waveform-based data; creating trustworthy and fair AI systems; and more. Contains 15 relevant, practice-oriented topics including AI and the imaging revolution; designing "living, breathing" clinical trials: lessons learned from the COVID-19 pandemic; the patient or the population: knowing the limitations of our data to make smart clinical decisions; weighing the cost vs. benefit of AI in healthcare; and more. Provides in-depth clinical reviews on data science in critical care, offering actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.
Toward Precision Medicine
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2012-01-16
Toward Precision Medicine written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-16 with Medical categories.
Motivated by the explosion of molecular data on humans-particularly data associated with individual patients-and the sense that there are large, as-yet-untapped opportunities to use this data to improve health outcomes, Toward Precision Medicine explores the feasibility and need for "a new taxonomy of human disease based on molecular biology" and develops a potential framework for creating one. The book says that a new data network that integrates emerging research on the molecular makeup of diseases with clinical data on individual patients could drive the development of a more accurate classification of diseases and ultimately enhance diagnosis and treatment. The "new taxonomy" that emerges would define diseases by their underlying molecular causes and other factors in addition to their traditional physical signs and symptoms. The book adds that the new data network could also improve biomedical research by enabling scientists to access patients' information during treatment while still protecting their rights. This would allow the marriage of molecular research and clinical data at the point of care, as opposed to research information continuing to reside primarily in academia. Toward Precision Medicine notes that moving toward individualized medicine requires that researchers and health care providers have access to very large sets of health- and disease-related data linked to individual patients. These data are also critical for developing the information commons, the knowledge network of disease, and ultimately the new taxonomy.
Precision Medicine And Artificial Intelligence
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Author : Michael Mahler
language : en
Publisher: Academic Press
Release Date : 2021-03-12
Precision Medicine And Artificial Intelligence written by Michael Mahler and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-12 with Science categories.
Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions Provides background, milestone and examples of precision medicine Outlines the paradigm shift towards precision medicine driven by value-based systems Discusses future applications of precision medicine research using AI Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine