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Personalized Predictive Modeling in Type 1 Diabetes

Personalized Predictive Modeling in Type 1 Diabetes
A Book

by Eleni I. Georga,Dimitrios I Fotiadis,Stelios K. Tigas

  • Publisher : Academic Press
  • Release : 2017-12-11
  • Pages : 252
  • ISBN : 0128051469
  • Language : En, Es, Fr & De
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Personalized Predictive Modeling in Diabetes features state-of-the-art methodologies and algorithmic approaches which have been applied to predictive modeling of glucose concentration, ranging from simple autoregressive models of the CGM time series to multivariate nonlinear regression techniques of machine learning. Developments in the field have been analyzed with respect to: (i) feature set (univariate or multivariate), (ii) regression technique (linear or non-linear), (iii) learning mechanism (batch or sequential), (iv) development and testing procedure and (v) scaling properties. In addition, simulation models of meal-derived glucose absorption and insulin dynamics and kinetics are covered, as an integral part of glucose predictive models. This book will help engineers and clinicians to: select a regression technique which can capture both linear and non-linear dynamics in glucose metabolism in diabetes, and which exhibits good generalization performance under stationary and non-stationary conditions; ensure the scalability of the optimization algorithm (learning mechanism) with respect to the size of the dataset, provided that multiple days of patient monitoring are needed to obtain a reliable predictive model; select a features set which efficiently represents both spatial and temporal dependencies between the input variables and the glucose concentration; select simulation models of subcutaneous insulin absorption and meal absorption; identify an appropriate validation procedure, and identify realistic performance measures. Describes fundamentals of modeling techniques as applied to glucose control Covers model selection process and model validation Offers computer code on a companion website to show implementation of models and algorithms Features the latest developments in the field of diabetes predictive modeling

Neural Information Processing

Neural Information Processing
26th International Conference, ICONIP 2019, Sydney, NSW, Australia, December 12–15, 2019, Proceedings

by Tom Gedeon,Kok Wai Wong,Minho Lee

  • Publisher : Springer Nature
  • Release : 2019-12-10
  • Pages : 649
  • ISBN : 3030367185
  • Language : En, Es, Fr & De
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The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 11955, is organized in topical sections on semantic and graph based approaches; spiking neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models.

Data-driven Modeling for Diabetes

Data-driven Modeling for Diabetes
Diagnosis and Treatment

by Vasilis Marmarelis,Georgios Mitsis

  • Publisher : Springer Science & Business
  • Release : 2014-04-22
  • Pages : 237
  • ISBN : 3642544649
  • Language : En, Es, Fr & De
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This contributed volume presents computational models of diabetes that quantify the dynamic interrelationships among key physiological variables implicated in the underlying physiology under a variety of metabolic and behavioral conditions. These variables comprise for example blood glucose concentration and various hormones such as insulin, glucagon, epinephrine, norepinephrine as well as cortisol. The presented models provide a powerful diagnostic tool but may also enable treatment via long-term glucose regulation in diabetics through closed-look model-reference control using frequent insulin infusions, which are administered by implanted programmable micro-pumps. This research volume aims at presenting state-of-the-art research on this subject and demonstrating the potential applications of modeling to the diagnosis and treatment of diabetes. The target audience primarily comprises research and experts in the field but the book may also be beneficial for graduate students.

Neural Information Processing

Neural Information Processing
16th International Conference, ICONIP 2009, Bangkok, Thailand, December 1-5, 2009, Proceedings

by Chi-Sing Leung,Minho Lee,Jonathan H. Chan

  • Publisher : Springer Science & Business Media
  • Release : 2009-11-24
  • Pages : 888
  • ISBN : 364210682X
  • Language : En, Es, Fr & De
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The two volumes LNCS 5863 and 5864 constitute the proceedings of the 16th International Conference on Neural Information Processing, ICONIP 2009, held in Bangkok, Thailand, in December 2009. The 145 regular session papers and 53 special session papers presented were carefully reviewed and selected from 466 submissions. The papers are structured in topical sections on cognitive science and computational neuroscience, neurodynamics, mathematical modeling and analysis, kernel and related methods, learning algorithms, pattern analysis, face analysis and processing, image processing, financial applications, computer vision, control and robotics, evolutionary computation, other emerging computational methods, signal, data and text processing, artificial spiking neural systems: nonlinear dynamics and engineering applications, towards brain-inspired systems, computational advances in bioinformatics, data mining for cybersecurity, evolutionary neural networks: theory and practice, hybrid and adaptive systems for computer vision and robot control, intelligent data mining, neural networks for data mining, and SOM and related subjects and its applications.

FIRST ASSESSMENT OF THE PERFORMANCE OF A PERSONALIZED MACHINE LEARNING APPROACH TO PREDICTING BLOOD GLUCOSE LEVELS IN PATIENTS WITH TYPE 1 DIABETES: THE CDDIAB STUDY.

FIRST ASSESSMENT OF THE PERFORMANCE OF A PERSONALIZED MACHINE LEARNING APPROACH TO PREDICTING BLOOD GLUCOSE LEVELS IN PATIENTS WITH TYPE 1 DIABETES: THE CDDIAB STUDY.
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2017
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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BackgroundPatients with type 1 diabetes (T1D) make their decisions for insulin delivery from available past and present blood glucose (BG) data and the expected effects on BG of forthcoming meals and activities according to education rules and their own experience. Enriched information on predicted BG glucose evolution could help them in better tuning insulin therapy. CDDIAB studyu2019s objective was to evaluate a new machine learning approach to predicting BG levels of each individual from a collection of personal BG measurements with contextual data.MethodsFourteen patients with T1D (8F/6M, age: 51+/-15, T1D duration: 26+/-17 years, HbA1c: 7.09+/-0.82%), treated by insulin pump (n=11) or multiple daily insulin injections (n=3) volunteered to track BG using FreeStyle Libre (n=12), Enlite (n=1) or Dexcom G4 (n=1) CGM devices and log manually meal intakes and insulin doses for 30 days. Collected data were used to design patient-specific prediction models with 30- to 90-min horizons. The algorithms were initially fitted on a training dataset corresponding to an average of 9 days, using a 5-fold cross-validation method. The remaining days of available data were used to provide an unbiased evaluation of final models.ResultsThe MARD (Mean Absolute Relative Deviation) and the consensus Error Grid Analysis were used to evaluate accuracy of BG predictions for 30- to 90-min horizons, Our results, detailed below, show the MARD and percentage of points in zones A+B on a Parkes EGA:- At 30 minutes: MARD of 6.98%u00b12.0, and 99.93%u00b10.13,- At 60 minutes: MARD of 14.78%u00b13.25, and 98.56%u00b11.00,- At 90 minutes: MARD of 20.78%u00b14.08, and 96.29%u00b12.15.ConclusionPrediction algorithms showed promising results since 99.9, 98.6 and 96.3% of computed BG values were in EGA A+B zones at 30-, 60- and 90-min horizons, respectively. The integration into the training process of collected data by an activity tracker could further improve accuracy in future developments of the algorithm.Integrated inside a mobile application to support decision-making process, this technology could help patients anticipate and avoid upcoming occurrence of hypoglycaemia and hyperglycaemia, in particular during night time. It could also be used on top of an Artificial Pancreas MPC model, allowing for more personalization and better regulation of the system, particularly during unstable phases with rapid glucose changes.

Genomic and Personalized Medicine

Genomic and Personalized Medicine
A Book

by Anonim

  • Publisher : Academic Press
  • Release : 2008-11-11
  • Pages : 1558
  • ISBN : 9780080919034
  • Language : En, Es, Fr & De
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This two-volume set — winner of a 2013 Highly Commended BMA Medical Book Award for Medicine — provides an in-depth look at one of the most promising avenues for advances in the diagnosis, prevention and treatment of human disease. The inclusion of the latest information on diagnostic testing, population screening, predicting disease susceptibility, pharmacogenomics and more presents this book as an essential tool for both students and specialists across many biological and medical disciplines, including human genetics and genomics, oncology, neuroscience, cardiology, infectious disease, molecular medicine, and biomedical science, as well as health policy disciplines focusing on ethical, legal, regulatory and economic aspects of genomics and medicine. Volume One Includes: Principles, Methodology and Translational Approaches, takes readers on the journey from principles of human genomics to technology, informatic and computational platforms for genomic medicine, as well as strategies for translating genomic discoveries into advances in personalized clinical care. Volume Two Includes: Genome Discoveries and Clinical Applications presents the latest developments in disease-based genomic and personalized medicine. With chapters dedicated to cardiovascular disease, oncology, inflammatory disease, metabolic disease, neuropsychiatric disease, and infectious disease, this work provides the most comprehensive guide to the principles and practice of genomic and personalized medicine. Highly Commended 2013 BMA Medical Book Award for Medicine Contributions from leaders in the field provide unparalleled insight into current technologies and applications in clinical medicine. Full colour throughout enhances the utility of this work as the only available comprehensive reference for genomic and personalized medicine. Discusses scientific foundations and practical applications of new discoveries, as well as ethical, legal/regulatory, and social issues related to the practice of genomic medicine.

Prediction Methods for Blood Glucose Concentration

Prediction Methods for Blood Glucose Concentration
Design, Use and Evaluation

by Harald Kirchsteiger,John Bagterp Jørgensen,Eric Renard,Luigi del Re

  • Publisher : Springer
  • Release : 2015-11-24
  • Pages : 265
  • ISBN : 331925913X
  • Language : En, Es, Fr & De
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This book tackles the problem of overshoot and undershoot in blood glucose levels caused by delay in the effects of carbohydrate consumption and insulin administration. The ideas presented here will be very important in maintaining the welfare of insulin-dependent diabetics and avoiding the damaging effects of unpredicted swings in blood glucose – accurate prediction enables the implementation of counter-measures. The glucose prediction algorithms described are also a key and critical ingredient of automated insulin delivery systems, the so-called “artificial pancreas”. The authors address the topic of blood-glucose prediction from medical, scientific and technological points of view. Simulation studies are utilized for complementary analysis but the primary focus of this book is on real applications, using clinical data from diabetic subjects. The text details the current state of the art by surveying prediction algorithms, and then moves beyond it with the most recent advances in data-based modeling of glucose metabolism. The topic of performance evaluation is discussed and the relationship of clinical and technological needs and goals examined with regard to their implications for medical devices employing prediction algorithms. Practical and theoretical questions associated with such devices and their solutions are highlighted. This book shows researchers interested in biomedical device technology and control researchers working with predictive algorithms how incorporation of predictive algorithms into the next generation of portable glucose measurement can make treatment of diabetes safer and more efficient.

Textbook of Personalized Medicine

Textbook of Personalized Medicine
A Book

by Kewal K. Jain

  • Publisher : Springer Nature
  • Release : 2020-12-05
  • Pages : 744
  • ISBN : 3030620808
  • Language : En, Es, Fr & De
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This book is for personalized medicine as a prescription of specific treatments and therapeutics best suited for an individual and considers genetic as well as environmental factors that influence responses to therapy. Best approaches are described for integration of all available technologies for optimizing the therapy of individual patients. This comprehensive third edition covers the latest advances in personalized medicine and several chapters are devoted to various specialties, particulary cancer which is the largest area of application. The book discusses the development of personalized medicine and various players in it such as companies, academic institutions, the government, and the public as the consumer of healthcare. Additionally, the roles of bioinformatics, electronic health records, and digital technologies for personalized medicine are discussed. Textbook of Personalized Medicine, 3rd Edition serves as a convenient source of information for students at many levels and in a wide range of fields, including physicians, scientists, and decision makers in the biopharmaceutical and healthcare industries.

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
12th International Conference, EANN 2011 and 7th IFIP WG 12.5 International Conference, AIAI 2011, Corfu, Greece, September 15-18, 2011, Proceedings

by Lazaros S. Iliadis,Chrisina Jayne

  • Publisher : Springer Science & Business Media
  • Release : 2011-09-08
  • Pages : 532
  • ISBN : 3642239560
  • Language : En, Es, Fr & De
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The two-volume set IFIP AICT 363 and 364 constitutes the refereed proceedings of the 12th International Conference on Engineering Applications of Neural Networks, EANN 2011, and the 7th IFIP WG 12.5 International Conference, AIAI 2011, held jointly in Corfu, Greece, in September 2011. The 52 revised full papers and 28 revised short papers presented together with 31 workshop papers were carefully reviewed and selected from 150 submissions. The first volume includes the papers that were accepted for presentation at the EANN 2011 conference. They are organized in topical sections on computer vision and robotics, self organizing maps, classification/pattern recognition, financial and management applications of AI, fuzzy systems, support vector machines, learning and novel algorithms, reinforcement and radial basis function ANN, machine learning, evolutionary genetic algorithms optimization, Web applications of ANN, spiking ANN, feature extraction minimization, medical applications of AI, environmental and earth applications of AI, multi layer ANN, and bioinformatics. The volume also contains the accepted papers from the Workshop on Applications of Soft Computing to Telecommunication (ASCOTE 2011), the Workshop on Computational Intelligence Applications in Bioinformatics (CIAB 2011), and the Second Workshop on Informatics and Intelligent Systems Applications for Quality of Life Information Services (ISQLIS 2011).

EMBEC & NBC 2017

EMBEC & NBC 2017
Joint Conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC), Tampere, Finland, June 2017

by Hannu Eskola,Outi Väisänen,Jari Viik,Jari Hyttinen

  • Publisher : Springer
  • Release : 2017-06-12
  • Pages : 1139
  • ISBN : 9811051224
  • Language : En, Es, Fr & De
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This volume presents the proceedings of the joint conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC), held in Tampere, Finland, in June 2017. The proceedings present all traditional biomedical engineering areas, but also highlight new emerging fields, such as tissue engineering, bioinformatics, biosensing, neurotechnology, additive manufacturing technologies for medicine and biology, and bioimaging, to name a few. Moreover, it emphasizes the role of education, translational research, and commercialization.

Predictive Marketing

Predictive Marketing
Easy Ways Every Marketer Can Use Customer Analytics and Big Data

by Omer Artun,Dominique Levin

  • Publisher : John Wiley & Sons
  • Release : 2015-08-06
  • Pages : 272
  • ISBN : 1119037336
  • Language : En, Es, Fr & De
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Make personalized marketing a reality with this practical guideto predictive analytics Predictive Marketing is a predictive analytics primer fororganizations large and small, offering practical tips andactionable strategies for implementing more personalized marketingimmediately. The marketing paradigm is changing, and this bookprovides a blueprint for navigating the transition from creative-to data-driven marketing, from one-size-fits-all to one-on-one, andfrom marketing campaigns to real-time customer experiences. You'lllearn how to use machine-learning technologies to improve customeracquisition and customer growth, and how to identify and re-engageat-risk or lapsed customers by implementing an easy, automatedapproach to predictive analytics. Much more than just theory andtestament to the power of personalized marketing, this book focuseson action, helping you understand and actually begin using thisrevolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing areality. For the first time, predictive marketing is accessible toall marketers, not just those at large corporations — infact, many smaller organizations are leapfrogging their largercounterparts with innovative programs. This book shows you how tobring predictive analytics to your organization, with actionableguidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learningtechnology Base marketing decisions on concrete data rather than unprovenideas Marketers have long been talking about delivering personalizedexperiences across channels. All marketers want to deliverhappiness, but most still employ a one-size-fits-all approach.Predictive Marketing provides the information and insightyou need to lift your organization out of the campaign rut and intothe rarefied atmosphere of a truly personalized customerexperience.

Explainable AI in Healthcare and Medicine

Explainable AI in Healthcare and Medicine
Building a Culture of Transparency and Accountability

by Arash Shaban-Nejad

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 329
  • ISBN : 3030533522
  • Language : En, Es, Fr & De
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Automated Reasoning for Systems Biology and Medicine

Automated Reasoning for Systems Biology and Medicine
A Book

by Pietro Liò,Paolo Zuliani

  • Publisher : Springer
  • Release : 2019-06-11
  • Pages : 474
  • ISBN : 303017297X
  • Language : En, Es, Fr & De
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This book presents outstanding contributions in an exciting, new and multidisciplinary research area: the application of formal, automated reasoning techniques to analyse complex models in systems biology and systems medicine. Automated reasoning is a field of computer science devoted to the development of algorithms that yield trustworthy answers, providing a basis of sound logical reasoning. For example, in the semiconductor industry formal verification is instrumental to ensuring that chip designs are free of defects (or “bugs”). Over the past 15 years, systems biology and systems medicine have been introduced in an attempt to understand the enormous complexity of life from a computational point of view. This has generated a wealth of new knowledge in the form of computational models, whose staggering complexity makes manual analysis methods infeasible. Sound, trusted, and automated means of analysing the models are thus required in order to be able to trust their conclusions. Above all, this is crucial to engineering safe biomedical devices and to reducing our reliance on wet-lab experiments and clinical trials, which will in turn produce lower economic and societal costs. Some examples of the questions addressed here include: Can we automatically adjust medications for patients with multiple chronic conditions? Can we verify that an artificial pancreas system delivers insulin in a way that ensures Type 1 diabetic patients never suffer from hyperglycaemia or hypoglycaemia? And lastly, can we predict what kind of mutations a cancer cell is likely to undergo? This book brings together leading researchers from a number of highly interdisciplinary areas, including: · Parameter inference from time series · Model selection · Network structure identification · Machine learning · Systems medicine · Hypothesis generation from experimental data · Systems biology, systems medicine, and digital pathology · Verification of biomedical devices “This book presents a comprehensive spectrum of model-focused analysis techniques for biological systems ...an essential resource for tracking the developments of a fast moving field that promises to revolutionize biology and medicine by the automated analysis of models and data.”Prof Luca Cardelli FRS, University of Oxford

Predictive Analytics For Dummies

Predictive Analytics For Dummies
A Book

by Dr. Anasse Bari,Mohamed Chaouchi,Tommy Jung

  • Publisher : John Wiley & Sons
  • Release : 2014-03-06
  • Pages : 360
  • ISBN : 1118729412
  • Language : En, Es, Fr & De
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Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big Data Predictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businesses Helps readers see how to shepherd predictive analytics projects through their companies Explains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and more Covers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data Also covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewhere Propose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies.

Intelligent Systems and Applications

Intelligent Systems and Applications
Proceedings of the 2019 Intelligent Systems Conference (IntelliSys)

by Yaxin Bi,Rahul Bhatia,Supriya Kapoor

  • Publisher : Springer Nature
  • Release : 2019-08-23
  • Pages : 1312
  • ISBN : 3030295133
  • Language : En, Es, Fr & De
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The book presents a remarkable collection of chapters covering a wide range of topics in the areas of intelligent systems and artificial intelligence, and their real-world applications. It gathers the proceedings of the Intelligent Systems Conference 2019, which attracted a total of 546 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-review process, after which 190 were selected for inclusion in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made it possible to tackle a host of problems more effectively. This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for an international conference as a venue for reporting on the latest innovations and trends. This book collects both theory and application based chapters on virtually all aspects of artificial intelligence; presenting state-of-the-art intelligent methods and techniques for solving real-world problems, along with a vision for future research, it represents a unique and valuable asset.

Medical Management of Diabetes Mellitus

Medical Management of Diabetes Mellitus
A Book

by William T. Cefalu

  • Publisher : CRC Press
  • Release : 2000-02-17
  • Pages : 768
  • ISBN : 9781420001631
  • Language : En, Es, Fr & De
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This book is a how-to manual for practicing physicians and health care providers, nurse educators, nutritionists, and physicians in training in the management of persons with diabetes mellitus. Experts with strong clinical and teaching backgrounds provide up-to-date recom-mendations and rationale of the most effective diagnostic and therapeutic app

Fundamentals of Clinical Data Science

Fundamentals of Clinical Data Science
A Book

by Pieter Kubben,Michel Dumontier,Andre Dekker

  • Publisher : Springer
  • Release : 2018-12-21
  • Pages : 219
  • ISBN : 3319997130
  • Language : En, Es, Fr & De
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This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

Artificial Intelligence In Medicine

Artificial Intelligence In Medicine
A Book

by Peter Szolovits

  • Publisher : Routledge
  • Release : 2019-03-13
  • Pages : 226
  • ISBN : 0429728468
  • Language : En, Es, Fr & De
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This book introduces the field of artificial intelligence in medicine, a new research area that combines sophisticated representational and computing techniques with the insights of expert physicians to produce tools for improving health care. An introductory chapter describes the historical and technical foundations of the work and provides an overview of the current state of the art and research directions. The authors then describe four prototype computer programs that tackle difficult clinical problems in a manner similar to that of an expert physician. The programs presented are internist, a diagnostic aid that combines a large database of disease/manifestation associations with techniques for problem formulation; expert and the Glaucoma Program which use physiological models for the diagnosis and treatment of eye disease; mycin, a rule-based program for diagnosis and therapy selection for infectious diseases; and the Digitalis Therapy Advisor, which aids the physician in prescribing the right dose of the drug digitalis and also explains its actions.

New Strategies to Advance Pre/Diabetes Care: Integrative Approach by PPPM

New Strategies to Advance Pre/Diabetes Care: Integrative Approach by PPPM
A Book

by Mahmood S. Mozaffari

  • Publisher : Springer Science & Business Media
  • Release : 2013-03-13
  • Pages : 538
  • ISBN : 9400759711
  • Language : En, Es, Fr & De
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This book is intended to provide up-to-date and emerging information in the field of diabetes mellitus with a focus on preventive, predictive and personalized medicine.

Modelling Methodology for Physiology and Medicine

Modelling Methodology for Physiology and Medicine
A Book

by Ewart Carson,Claudio Cobelli

  • Publisher : Newnes
  • Release : 2013-12-05
  • Pages : 588
  • ISBN : 0124095259
  • Language : En, Es, Fr & De
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Modelling Methodology for Physiology and Medicine, Second Edition, offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modeling methodology that is widely applicable to physiology and medicine. The second edition, which is completely updated and expanded, opens with a clear and integrated treatment of advanced methodology for developing mathematical models of physiology and medical systems. Readers are then shown how to apply this methodology beneficially to real-world problems in physiology and medicine, such as circulation and respiration. The focus of Modelling Methodology for Physiology and Medicine, Second Edition, is the methodology that underpins good modeling practice. It builds upon the idea of an integrated methodology for the development and testing of mathematical models. It covers many specific areas of methodology in which important advances have taken place over recent years and illustrates the application of good methodological practice in key areas of physiology and medicine. It builds on work that the editors have carried out over the past 30 years, working in cooperation with leading practitioners in the field. Builds upon and enhances the reader's existing knowledge of modeling methodology and practice Editors are internationally renowned leaders in their respective fields Provides an understanding of modeling methodologies that can address real problems in physiology and medicine and achieve results that are beneficial either in advancing research or in providing solutions to clinical problems