Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2022 written by Linwei Wang and published by Springer Nature. This book was released on 2022-09-15 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt: The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging; Part III: Breast imaging; colonoscopy; computer aided diagnosis; Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I; Part V: Image segmentation II; integration of imaging with non-imaging biomarkers; Part VI: Image registration; image reconstruction; Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization; Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies.
Download or read book Few Shot Machine Learning written by Robert Johnson and published by HiTeX Press. This book was released on 2024-10-27 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Few-Shot Machine Learning: Doing More with Less Data" is an illuminating exploration into the cutting-edge techniques that enable machines to learn efficiently from limited data. This book delves deep into the domain of few-shot learning—a revolutionary approach that challenges the traditional dependency on vast datasets. By uncovering the principles and practices that allow models to generalize from minimal examples, it empowers readers to harness the power of artificial intelligence in resource-constrained environments. Carefully structured to provide both theoretical insights and practical guidance, the book navigates through essential paradigms such as meta-learning, transfer learning, and innovative data augmentation strategies. It emphasizes the building blocks needed to understand and apply few-shot learning across various domains, from healthcare diagnostics to real-time analytics. Through real-world applications and case studies, the text not only illustrates the transformative potential of few-shot learning but also prepares practitioners to address prevalent challenges and seize future opportunities in this dynamic field. "Few-Shot Machine Learning: Doing More with Less Data" serves as an indispensable resource for beginners and experienced professionals alike, offering a comprehensive guide to leveraging advanced machine learning techniques. By presenting complex concepts in an accessible manner, it opens new pathways for creativity and innovation in artificial intelligence, making it an essential companion for anyone interested in the future of machine learning and data science.
Download or read book Applying Machine Learning Techniques to Bioinformatics Few Shot and Zero Shot Methods written by Lilhore, Umesh Kumar and published by IGI Global. This book was released on 2024-03-22 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientists ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges. The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics. This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences.
Download or read book Meta Learning With Medical Imaging and Health Informatics Applications written by Hien Van Nguyen and published by Academic Press. This book was released on 2022-09-24 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks' fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks.This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such as model-agnostic learning, memory augmentation, prototypical networks, and learning to optimize. The book brings together thought leaders from both machine learning and health informatics fields to discuss the current state of Meta-Learning, its relevance to medical imaging and health informatics, and future directions. - First book on applying Meta Learning to medical imaging - Pioneers in the field as contributing authors to explain the theory and its development - Has GitHub repository consisting of various code examples and documentation to help the audience to set up Meta-Learning algorithms for their applications quickly
Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2021 written by Marleen de Bruijne and published by Springer Nature. This book was released on 2021-09-23 with total page 873 pages. Available in PDF, EPUB and Kindle. Book excerpt: The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging – others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.
Download or read book Resource Efficient Medical Image Analysis written by Xinxing Xu and published by Springer Nature. This book was released on 2022-09-15 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the first MICCAI Workshop on Resource-Efficient Medical Image Analysis, REMIA 2022, held in conjunction with MICCAI 2022, in September 2022 as a hybrid event. REMIA 2022 accepted 13 papers from the 19 submissions received. The workshop aims at creating a discussion on the issues for practical applications of medical imaging systems with data, label and hardware limitations.
Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2020 written by Anne L. Martel and published by Springer Nature. This book was released on 2020-10-02 with total page 849 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography
Download or read book Neural Information Processing written by Mohammad Tanveer and published by Springer Nature. This book was released on 2023-04-12 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 146 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Download or read book 2020 IEEE CVF Conference on Computer Vision and Pattern Recognition CVPR written by IEEE Staff and published by . This book was released on 2020-06-13 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: CVPR is the premier annual computer vision event comprising the main conference and several co located workshops and short courses With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers
Download or read book Artificial Intelligence and Machine Learning written by Hai Jin and published by Springer Nature. This book was released on with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Meta Learning written by Lan Zou and published by Elsevier. This book was released on 2022-11-05 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep neural networks (DNNs) with their dense and complex algorithms provide real possibilities for Artificial General Intelligence (AGI). Meta-learning with DNNs brings AGI much closer: artificial agents solving intelligent tasks that human beings can achieve, even transcending what they can achieve. Meta-Learning: Theory, Algorithms and Applications shows how meta-learning in combination with DNNs advances towards AGI. Meta-Learning: Theory, Algorithms and Applications explains the fundamentals of meta-learning by providing answers to these questions: What is meta-learning?; why do we need meta-learning?; how are self-improved meta-learning mechanisms heading for AGI ?; how can we use meta-learning in our approach to specific scenarios? The book presents the background of seven mainstream paradigms: meta-learning, few-shot learning, deep learning, transfer learning, machine learning, probabilistic modeling, and Bayesian inference. It then explains important state-of-the-art mechanisms and their variants for meta-learning, including memory-augmented neural networks, meta-networks, convolutional Siamese neural networks, matching networks, prototypical networks, relation networks, LSTM meta-learning, model-agnostic meta-learning, and the Reptile algorithm. The book takes a deep dive into nearly 200 state-of-the-art meta-learning algorithms from top tier conferences (e.g. NeurIPS, ICML, CVPR, ACL, ICLR, KDD). It systematically investigates 39 categories of tasks from 11 real-world application fields: Computer Vision, Natural Language Processing, Meta-Reinforcement Learning, Healthcare, Finance and Economy, Construction Materials, Graphic Neural Networks, Program Synthesis, Smart City, Recommended Systems, and Climate Science. Each application field concludes by looking at future trends or by giving a summary of available resources. Meta-Learning: Theory, Algorithms and Applications is a great resource to understand the principles of meta-learning and to learn state-of-the-art meta-learning algorithms, giving the student, researcher and industry professional the ability to apply meta-learning for various novel applications. A comprehensive overview of state-of-the-art meta-learning techniques and methods associated with deep neural networks together with a broad range of application areas Coverage of nearly 200 state-of-the-art meta-learning algorithms, which are promoted by premier global AI conferences and journals, and 300 to 450 pieces of key research Systematic and detailed exploration of the most crucial state-of-the-art meta-learning algorithm mechanisms: model-based, metric-based, and optimization-based Provides solutions to the limitations of using deep learning and/or machine learning methods, particularly with small sample sizes and unlabeled data Gives an understanding of how meta-learning acts as a stepping stone to Artificial General Intelligence in 39 categories of tasks from 11 real-world application fields
Download or read book Predictive Intelligence in Medicine written by Islem Rekik and published by Springer Nature. This book was released on 2021-09-27 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 4th International Workshop on Predictive Intelligence in Medicine, PRIME 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in October 2021.* The 25 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine. *The workshop was held virtually.
Download or read book Neural Approaches to Dynamics of Signal Exchanges written by Anna Esposito and published by Springer Nature. This book was released on 2019-09-18 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents research that contributes to the development of intelligent dialog systems to simplify diverse aspects of everyday life, such as medical diagnosis and entertainment. Covering major thematic areas: machine learning and artificial neural networks; algorithms and models; and social and biometric data for applications in human–computer interfaces, it discusses processing of audio-visual signals for the detection of user-perceived states, the latest scientific discoveries in processing verbal (lexicon, syntax, and pragmatics), auditory (voice, intonation, vocal expressions) and visual signals (gestures, body language, facial expressions), as well as algorithms for detecting communication disorders, remote health-status monitoring, sentiment and affect analysis, social behaviors and engagement. Further, it examines neural and machine learning algorithms for the implementation of advanced telecommunication systems, communication with people with special needs, emotion modulation by computer contents, advanced sensors for tracking changes in real-life and automatic systems, as well as the development of advanced human–computer interfaces. The book does not focus on solving a particular problem, but instead describes the results of research that has positive effects in different fields and applications.
Download or read book Chasing My Cure written by David Fajgenbaum and published by Ballantine Books. This book was released on 2019-09-10 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: LOS ANGELES TIMES AND PUBLISHERS WEEKLY BESTSELLER • The powerful memoir of a young doctor and former college athlete diagnosed with a rare disease who spearheaded the search for a cure—and became a champion for a new approach to medical research. “A wonderful and moving chronicle of a doctor’s relentless pursuit, this book serves both patients and physicians in demystifying the science that lies behind medicine.”—Siddhartha Mukherjee, New York Times bestselling author of The Emperor of All Maladies and The Gene David Fajgenbaum, a former Georgetown quarterback, was nicknamed the Beast in medical school, where he was also known for his unmatched mental stamina. But things changed dramatically when he began suffering from inexplicable fatigue. In a matter of weeks, his organs were failing and he was read his last rites. Doctors were baffled by his condition, which they had yet to even diagnose. Floating in and out of consciousness, Fajgenbaum prayed for a second chance, the equivalent of a dramatic play to second the game into overtime. Miraculously, Fajgenbaum survived—only to endure repeated near-death relapses from what would eventually be identified as a form of Castleman disease, an extremely deadly and rare condition that acts like a cross between cancer and an autoimmune disorder. When he relapsed while on the only drug in development and realized that the medical community was unlikely to make progress in time to save his life, Fajgenbaum turned his desperate hope for a cure into concrete action: Between hospitalizations he studied his own charts and tested his own blood samples, looking for clues that could unlock a new treatment. With the help of family, friends, and mentors, he also reached out to other Castleman disease patients and physicians, and eventually came up with an ambitious plan to crowdsource the most promising research questions and recruit world-class researchers to tackle them. Instead of waiting for the scientific stars to align, he would attempt to align them himself. More than five years later and now married to his college sweetheart, Fajgenbaum has seen his hard work pay off: A treatment he identified has induced a tentative remission and his novel approach to collaborative scientific inquiry has become a blueprint for advancing rare disease research. His incredible story demonstrates the potency of hope, and what can happen when the forces of determination, love, family, faith, and serendipity collide. Praise for Chasing My Cure “A page-turning chronicle of living, nearly dying, and discovering what it really means to be invincible in hope.”—Angela Duckworth, #1 New York Times bestselling author of Grit “[A] remarkable memoir . . . Fajgenbaum writes lucidly and movingly . . . Fajgenbaum’s stirring account of his illness will inspire readers.”—Publishers Weekly
Download or read book Machine Learning Algorithms for Industrial Applications written by Santosh Kumar Das and published by Springer Nature. This book was released on 2020-07-18 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.
Download or read book Bioinformatics Research and Applications written by Wei Peng and published by Springer Nature. This book was released on with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Augmentation Labelling and Imperfections written by Hien V. Nguyen and published by Springer Nature. This book was released on 2022-09-21 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2022, held in conjunction with MICCAI 2022, in Singapore in September 2022. DALI 2022 accepted 12 papers from the 22 submissions that were reviewed. The papers focus on rigorous study of medical data related to machine learning systems.
