Proceedings of 2023 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2023) PDF Download
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Author: Ruidan Su
Publisher: Springer Nature
ISBN: 9819713358
Category :
Languages : en
Pages : 414
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Book Description
Author: Ruidan Su
Publisher: Springer Nature
ISBN: 9819713358
Category :
Languages : en
Pages : 414
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Book Description
Author: Debasis Chaudhuri
Publisher: CRC Press
ISBN: 1040052487
Category : Computers
Languages : en
Pages : 468
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Book Description
The International Conference on Security, Surveillance & Artificial Intelligence (ICSSAI2023) was held in West Bengal, India during December 1–2, 2023. The conference was organized by the Techno India University, one of the renowned universities in the state of West Bengal which is committed for generating, disseminating and preserving knowledge.
Author: Manjaree Pandit
Publisher: Springer Nature
ISBN: 9819703271
Category :
Languages : en
Pages : 714
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Book Description
Author: Ruidan Su
Publisher: Springer Nature
ISBN: 9811667756
Category : Technology & Engineering
Languages : en
Pages : 567
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Book Description
This book covers virtually all aspects of image formation in medical imaging, including systems based on ionizing radiation (x-rays, gamma rays) and non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike. In addition, it discusses the development and application of computer-aided detection and diagnosis (CAD) systems in medical imaging. Given its coverage, the book provides both a forum and valuable resource for researchers involved in image formation, experimental methods, image performance, segmentation, pattern recognition, feature extraction, classifier design, machine learning / deep learning, radiomics, CAD workstation design, human–computer interaction, databases, and performance evaluation.
Author: Islem Rekik
Publisher: Springer Nature
ISBN: 3031460057
Category : Computers
Languages : en
Pages : 306
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Book Description
This volume LNCS 14277 constitutes the refereed proceedings of the 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, in October 2023, held in Vancouver, BC, Canada. The 24 full papers presented were carefully reviewed and selected from 27 submissions. This workshop intersects ideas from both machine learning and mathematical/statistical/physical modeling research directions in the hope to provide a deeper understanding of the foundations of predictive intelligence developed for medicine, as well as to where we currently stand and what we aspire to achieve through this field.
Author: Brandon K. K. Fields
Publisher: Frontiers Media SA
ISBN: 2832556418
Category : Medical
Languages : en
Pages : 119
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Book Description
Increasing interest in the development and validation of quantitative imaging biomarkers for oncologic imaging has in recent years inspired a surge in the field of artificial intelligence and machine learning. Initial results showed promise in identifying potential markers of treatment response, malignant potential, and prognostic predictors, among others; however, while many of these early algorithms showed the optimistic ability to separate pathologic states on “in-house” datasets, it was often the case that these classifiers generalized poorly on external validation sets and thus were of limited utility in the clinical setting. This issue was additionally compounded by the frequent use of data filtering and feature selection techniques in many studies to further bolster the machine learning results in limited case scenarios, thereby biasing the overall fit and further reducing generalizability.
Author: Dubey, Archi
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 468
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Book Description
The healthcare industry is increasingly complex, demanding personalized treatments and efficient operational processes. Traditional research methods need help to keep pace with these demands, often leading to inefficiencies and suboptimal outcomes. Integrating digital twin technology presents a promising solution to these challenges, offering a virtual platform for modeling and simulating complex healthcare scenarios. However, the full potential of digital twins still needs to be explored mainly due to a lack of comprehensive guidance and practical insights for researchers and practitioners. Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0 is not just a theoretical exploration. It is a practical guide that bridges the gap between theory and practice, offering real-world case studies, best practices, and insights into personalized medicine, real-time patient monitoring, and healthcare process optimization. By equipping you with the knowledge and tools needed to effectively integrate digital twins into your healthcare research and operations, this book is a valuable resource for researchers, academicians, medical practitioners, scientists, and students.
Author: Samia Bouzefrane
Publisher: Springer Nature
ISBN: 3031603915
Category :
Languages : en
Pages : 205
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Book Description
Author: Ruidan Su
Publisher: Springer Nature
ISBN: 9811638802
Category : Technology & Engineering
Languages : en
Pages : 447
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Book Description
This book covers virtually all aspects of image formation in medical imaging, including systems based on ionizing radiation (x-rays, gamma rays) and non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike. In addition, it discusses the development and application of computer-aided detection and diagnosis (CAD) systems in medical imaging. Also there will be a special track on computer-aided diagnosis on COVID-19 by CT and X-rays images. Given its coverage, the book provides both a forum and valuable resource for researchers involved in image formation, experimental methods, image performance, segmentation, pattern recognition, feature extraction, classifier design, machine learning / deep learning, radiomics, CAD workstation design, human–computer interaction, databases, and performance evaluation.
Author: Carlotta A. Berry
Publisher: McGraw Hill Professional
ISBN: 126492271X
Category : Technology & Engineering
Languages : en
Pages : 249
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Book Description
This practical guide shows, step by step, how to use machine learning to carry out actionable decisions that do not discriminate based on numerous human factors, including ethnicity and gender. The authors examine the many kinds of bias that occur in the field today and provide mitigation strategies that are ready to deploy across a wide range of technologies, applications, and industries. Edited by engineering and computing experts, Mitigating Bias in Machine Learning includes contributions from recognized scholars and professionals working across different artificial intelligence sectors. Each chapter addresses a different topic and real-world case studies are featured throughout that highlight discriminatory machine learning practices and clearly show how they were reduced. Mitigating Bias in Machine Learning addresses: Ethical and Societal Implications of Machine Learning Social Media and Health Information Dissemination Comparative Case Study of Fairness Toolkits Bias Mitigation in Hate Speech Detection Unintended Systematic Biases in Natural Language Processing Combating Bias in Large Language Models Recognizing Bias in Medical Machine Learning and AI Models Machine Learning Bias in Healthcare Achieving Systemic Equity in Socioecological Systems Community Engagement for Machine Learning
