ISBI 2019 C-NMC Challenge: Classification in Cancer Cell Imaging
ISBI 2019 C-NMC Challenge: Classification in Cancer Cell Imaging

Author: Anubha Gupta

Publisher: Springer Nature

Published: 2019-11-28

Total Pages: 150

ISBN-13: 9811507988

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This book comprises select peer-reviewed proceedings of the medical challenge - C-NMC challenge: Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images. The challenge was run as part of the IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2019 held at Venice, Italy in April 2019. Cell classification via image processing has recently gained interest from the point of view of building computer-assisted diagnostic tools for blood disorders such as leukaemia. In order to arrive at a conclusive decision on disease diagnosis and degree of progression, it is very important to identify malignant cells with high accuracy. Computer-assisted tools can be very helpful in automating the process of cell segmentation and identification because morphologically both cell types appear similar. This particular challenge was run on a curated data set of more than 14000 cell images of very high quality. More than 200 international teams participated in the challenge. This book covers various solutions using machine learning and deep learning approaches. The book will prove useful for academics, researchers, and professionals interested in building low-cost automated diagnostic tools for cancer diagnosis and treatment.

State of the Art in Neural Networks and Their Applications
State of the Art in Neural Networks and Their Applications

Author: Jasjit Suri

Publisher: Elsevier

Published: 2022-11-29

Total Pages: 328

ISBN-13: 0128199121

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State of the Art in Neural Networks and Their Applications, Volume Two presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. The book provides over views and case studies of advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing, and suitable data analytics useful for clinical diagnosis and research applications. The application of neural network, artificial intelligence and machine learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume One: Neural Networks in Oncology Imaging covers lung cancer, prostate cancer, and bladder cancer. Volume Two: Neural Networks in Brain Disorders and Other Diseases covers autism spectrum disorder, Alzheimer's disease, attention deficit hyperactivity disorder, hypertension, and other diseases. Written by experienced engineers in the field, these two volumes will help engineers, computer scientists, researchers, and clinicians understand the technology and applications of artificial neural networks. - Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of oncology imaging technologies - Provides in-depth technical coverage of computer-aided diagnosis (CAD), including coverage of computer-aided classification, unified deep learning frameworks, 3D MRI, PET/CT, and more - Covers deep learning cancer identification from histopathological images, medical image analysis, detection, segmentation and classification via AI

Pattern Recognition. ICPR International Workshops and Challenges
Pattern Recognition. ICPR International Workshops and Challenges

Author: Alberto Del Bimbo

Publisher: Springer Nature

Published: 2021-02-20

Total Pages: 741

ISBN-13: 3030687635

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This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.

AI Assurance
AI Assurance

Author: Feras A. Batarseh

Publisher: Academic Press

Published: 2022-10-12

Total Pages: 602

ISBN-13: 0323918824

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AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI provides readers with solutions and a foundational understanding of the methods that can be applied to test AI systems and provide assurance. Anyone developing software systems with intelligence, building learning algorithms, or deploying AI to a domain-specific problem (such as allocating cyber breaches, analyzing causation at a smart farm, reducing readmissions at a hospital, ensuring soldiers' safety in the battlefield, or predicting exports of one country to another) will benefit from the methods presented in this book. As AI assurance is now a major piece in AI and engineering research, this book will serve as a guide for researchers, scientists and students in their studies and experimentation. Moreover, as AI is being increasingly discussed and utilized at government and policymaking venues, the assurance of AI systems—as presented in this book—is at the nexus of such debates. - Provides readers with an in-depth understanding of how to develop and apply Artificial Intelligence in a valid, explainable, fair and ethical manner - Includes various AI methods, including Deep Learning, Machine Learning, Reinforcement Learning, Computer Vision, Agent-Based Systems, Natural Language Processing, Text Mining, Predictive Analytics, Prescriptive Analytics, Knowledge-Based Systems, and Evolutionary Algorithms - Presents techniques for efficient and secure development of intelligent systems in a variety of domains, such as healthcare, cybersecurity, government, energy, education, and more - Covers complete example datasets that are associated with the methods and algorithms developed in the book

Data Science and Network Engineering
Data Science and Network Engineering

Author: Suyel Namasudra

Publisher: Springer Nature

Published: 2023-11-02

Total Pages: 525

ISBN-13: 9819967554

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This book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2023) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 21–22, 2023. It includes research works from researchers, academicians, business executives, and industry professionals for solving real-life problems by using the advancements and applications of data science and network engineering. This book covers many advanced topics, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering.

Advances In Pattern Recognition And Artificial Intelligence
Advances In Pattern Recognition And Artificial Intelligence

Author: Marleah Blom

Publisher: World Scientific

Published: 2021-11-16

Total Pages: 277

ISBN-13: 9811239029

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This book includes reviewed papers by international scholars from the 2020 International Conference on Pattern Recognition and Artificial Intelligence (held online). The papers have been expanded to provide more details specifically for the book. It is geared to promote ongoing interest and understanding about pattern recognition and artificial intelligence. Like the previous book in the series, this book covers a range of topics and illustrates potential areas where pattern recognition and artificial intelligence can be applied. It highlights, for example, how pattern recognition and artificial intelligence can be used to classify, predict, detect and help promote further discoveries related to credit scores, criminal news, national elections, license plates, gender, personality characteristics, health, and more.Chapters include works centred on medical and financial applications as well as topics related to handwriting analysis and text processing, internet security, image analysis, database creation, neural networks and deep learning. While the book is geared to promote interest from the general public, it may also be of interest to graduate students and researchers in the field.

17th International Conference on Biomedical Engineering
17th International Conference on Biomedical Engineering

Author: Chwee Teck Lim

Publisher: Springer Nature

Published: 2021-01-11

Total Pages: 194

ISBN-13: 303062045X

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This book gathers contributions presented at the 17th International Conference on Biomedical Engineering, held on December 9-12, 2019, in Singapore. It continues the tradition of the previous conference proceedings, thus reporting on both fundamental and applied research. It includes a set of carefully selected chapters reporting on new models and algorithms and their applications in medical diagnosis or therapy. It also discusses advances in tele-health and assistive technologies, as well as applications of nanotechnologies. Organized jointly by the Department of Biomedical Engineering of the National University of Singapore and the Biomedical Engineering Society (Singapore), this book offers a timely snapshot of innovative research and technologies and a source of inspiration for future developments and collaborations in the field of biomedical engineering.

Predicting Pregnancy Complications Through Artificial Intelligence and Machine Learning
Predicting Pregnancy Complications Through Artificial Intelligence and Machine Learning

Author: Kumar, D. Satish

Publisher: IGI Global

Published: 2023-09-25

Total Pages: 386

ISBN-13: 1668489767

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Artificial intelligence models are being used to make labor and delivery safer for mothers and newborns. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. This is a critical area of study as maternal and infant health are indispensable for a healthy society. Predicting Pregnancy Complications Through Artificial Intelligence and Machine Learning considers the recent advances, challenges, and best practices of artificial intelligence and machine learning in relation to pregnancy complications. Covering key topics such as pregnancy complications, wearable sensors, and healthcare technologies, this premier reference source is ideal for nurses, doctors, computer scientists, medical professionals, industry professionals, researchers, academicians, scholars, instructors, and students.