machine learning medical applications (34 Ergebnisse)

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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 542 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018.The 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected.The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluatethe strengths and weaknesses of DL and identifythe main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018.The 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected. The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluate the strengths and weaknesses of DL and identifythe main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 168 pp. Englisch.

Taschenbuch. Zustand: Neu. Understanding and Interpreting Machine Learning in Medical Image Computing Applications | First International Workshops, MLCN 2018, DLF 2018, and iMIMIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018, Proceedings | Danail Stoyanov (u. a.) | Taschenbuch | xvi | Englisch | 2018 | Springer | EAN 9783030026271 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction.The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset.

Taschenbuch. Zustand: Neu. Machine Learning for Critical Internet of Medical Things | Applications and Use Cases | Anand Nayyar (u. a.) | Taschenbuch | x | Englisch | 2023 | Springer Nature Switzerland | EAN 9783030809300 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Zustand: Gut. Zustand: Gut | Seiten: 272 | Sprache: Englisch | Produktart: Bücher | This book discusses the applications, challenges, and future trends of machine learning in medical domain, including both basic and advanced topics. The book presents how machine learning is helpful in smooth conduction of administrative processes in hospitals, in treating infectious diseases, and in personalized medical treatments. The authors show how machine learning can also help make fast and more accurate disease diagnoses, easily identify patients, help in new types of therapies or treatments, model small-molecule drugs in pharmaceutical sector, and help with innovations via integrated technologies such as artificial intelligence as well as deep learning. The authors show how machine learning also improves the physician¿s and doctor¿s medical capabilities to better diagnosis their patients. This book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning that will enhance the efficiency and effectiveness of the healthcare system.Provides researchers in machine and deep learning with a conceptual understanding of various methodologies of implementing the technologies in medical areas;Discusses the role machine learning and IoT play into locating different virus and diseases across the globe, such as COVID-19, Ebola, and cervical cancer;Includes fundamentals and advances in machine learning in the medical field, supported by significant case studies and practical applications.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 550 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book discusses the applications, challenges, and future trends of machine learning in medical domain, including both basic and advanced topics. The book presents how machine learning is helpful in smooth conduction of administrative processes in hospitals, in treating infectious diseases, and in personalized medical treatments. The authors show how machine learning can also help make fast and more accurate disease diagnoses, easily identify patients, help in new types of therapies or treatments, model small-molecule drugs in pharmaceutical sector, and help with innovations via integrated technologies such as artificial intelligence as well as deep learning. The authors show how machine learning also improves the physician's and doctor's medical capabilities to better diagnosis their patients. This book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning that will enhance the efficiency and effectiveness of the healthcare system.Provides researchers in machine and deep learning with a conceptual understanding of various methodologies of implementing the technologies in medical areas;Discusses the role machine learning and IoT play into locating different virus and diseases across the globe, such as COVID-19, Ebola, and cervical cancer;Includes fundamentals and advances in machine learning in the medical field, supported by significant case studies and practical applications.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book discusses the applications, challenges, and future trends of machine learning in medical domain, including both basic and advanced topics. The book presents how machine learning is helpful in smooth conduction of administrative processes in hospitals, in treating infectious diseases, and in personalized medical treatments. The authors show how machine learning can also help make fast and more accurate disease diagnoses, easily identify patients, help in new types of therapies or treatments, model small-molecule drugs in pharmaceutical sector, and help with innovations via integrated technologies such as artificial intelligence as well as deep learning. The authors show how machine learning also improves the physician's and doctor's medical capabilities to better diagnosis their patients. This book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning that will enhance the efficiency and effectiveness of the healthcare system.Provides researchers in machine and deep learning with a conceptual understanding of various methodologies of implementing the technologies in medical areas;Discusses the role machine learning and IoT play into locating different virus and diseases across the globe, such as COVID-19, Ebola, and cervical cancer;Includes fundamentals and advances in machine learning in the medical field, supported by significant case studies and practical applications.

Buch. Zustand: Neu. Neuware - Machine Learning for Medical Applications - Volume I provides an in-depth look into the frontier of artificial intelligence in healthcare, bringing together contributions from leading researchers and innovators. This volume focuses on three critical areas: computational drug discovery, advanced bioimaging techniques, and the development of smart biomaterials for medical use. Readers will discover how machine learning is revolutionizing personalized medicine, improving diagnostic accuracy, and enabling the design of AI-driven biomedical sensors and therapeutic systems. With practical insights into algorithmic modeling, drug toxicity prediction, and materials screening, this book bridges the gap between data science and clinical applications. Ideal for professionals, academics, and students in biomedical engineering, computer science, and medical informatics, this book highlights the synergistic potential of machine learning and modern medicine in shaping the future of healthcare.

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Zustand: New. Sachi_Nandan_Mohanty_received_his_PhD_from_IIT_Kharagpur,_In dia_in_2015_and_is_now_at_ICFAI_Foundation_for_Higher_Educat ion,_Hyderabad,_IndiaJyotir_Moy_Chatterjee_is_working_as_an_ Assistant_Professor_IT_at_Lord_Buddha_Education_Foundation,_ Kathmandu,_Nepal_.