Prabhishek Singh - Böcker
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5 produkter
5 produkter
1 841 kr
Skickas inom 7-10 vardagar
Data-Driven Diagnostics and Disease Prediction with AI Optimization provides useful insights into model creation, data preparation, and ethical issues for healthcare applications. The book covers all the conventional and non-conventional methods related to this domain. It also discusses AI-based optimization techniques, Machine Learning models, and Advanced AI, offering practical insights, case studies, and optimization strategies to help data scientists and researchers efficiently employ AI in diagnostics and illness prediction in a world where precise diagnostics and early illness prediction may save lives and healthcare resources.Provides a complete overview of the challenges and pain points in implementing AI-driven diagnostics and disease prediction within the healthcare industryExplores various edge computing applications in healthcare and the use of hardware acceleration for AI applicationsPresents a comprehensive resource that bridges the gap between AI and healthcare
2 082 kr
Skickas inom 10-15 vardagar
The book aims to develop methodologies and throw light on the advances in empirical research of various machine learning systems through data mining and parallel programming using GPU approaches. It reviews concepts of existing machine learning and deep learning techniques and how these can be implemented in GPU computing with CUDA architecture. The book also discusses modern machine learning techniques for effective big data management in accordance with worldwide standards in the field.Covering diverse areas, this publication is meant for academicians, data scientists, industrial professionals, researchers and students interested in uncovering the latest innovations in the field.
Del 11 - Engineering Cyber-Physical Systems and Critical Infrastructures
Healthcare Industry Assessment: Analyzing Risks, Security, and Reliability
Inbunden, Engelska, 2024
2 181 kr
Skickas inom 10-15 vardagar
This resource provides valuable perspectives on the risks and difficulties currently faced by the healthcare industry and presents practical recommendations for effectively managing these risks and enhancing security and reliability.
Machine Learning and Deep Learning Modeling and Algorithms with Applications in Medical and Health Care
Inbunden, Engelska, 2025
1 485 kr
Skickas inom 7-10 vardagar
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.
3 471 kr
Kommande
This book offers a comprehensive study of medical image processing, with an emphasis on methods to enhance the accuracy and readability of medical images for diagnosis and therapy. Its main goals are to improve the visual clarity of images by sharpening details, lowering noise, and altering contrast to better visualize subtle elements. Also, it guarantees that anatomical features are accurately represented by correcting distortions, artefacts, and defects resulting from capture or transmission. Reconstruction is the main topic, including how to mix data from different modalities (such as CT and MRI) to build a more complete perspective or recreate missing or incomplete data from fragmented images. This book covers a wide range of topics, including deep learning methodologies, image processing methods, clinical applications, evaluation, and validation. The goal of the book is to provide readers a thorough understanding of medical image processing methods for enhancing, restoring, and reconstructing medical images. It describes the different algorithms’ theoretical foundations and real-world applications. It highlights the practical uses and promise of these methods for enhancing medical diagnosis and care.