A Beginner Guide To Medical Application Development With Deep Convolutional Neural Networks
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A Beginner Guide To Medical Application Development With Deep Convolutional Neural Networks
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Author : Snehan Biswas
language : en
Publisher:
Release Date : 2024-11
A Beginner Guide To Medical Application Development With Deep Convolutional Neural Networks written by Snehan Biswas and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11 with Medical categories.
"This book serves as source of introductory material and reference for medical application development and related technologies by providing the detail implementation of the cutting-edge deep learning methodologies. It targets the cloud based advanced medical application developments using open-source python based deep learning libraries. It includes code snippets and sophisticated Convolutional Neural Networks (CNNs) to tackle real-world problems in medical image analysis and beyond. The book provides programming guidance for creation of sophisticated and reliable neural networks for image processing and incorporates the comparative study on GAN, Stable diffusion and its application on Medical Image data augmentation. It focusses on solving real world medical imaging problems and discuses advanced concepts of Deep Learning along with latest technology like GPT, Stable Diffusion, ViT. This book is aimed at graduate students and researchers in medical data analytics, medical image analysis, signal processing, and deep learning"--
A Beginner S Guide To Medical Application Development With Deep Convolutional Neural Networks
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Author : Snehan Biswas
language : en
Publisher: CRC Press
Release Date : 2024-12-02
A Beginner S Guide To Medical Application Development With Deep Convolutional Neural Networks written by Snehan Biswas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-02 with Technology & Engineering categories.
This book serves as a source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of cutting-edge deep learning methodologies. It targets cloud-based advanced medical application developments using open-source Python-based deep learning libraries. It includes code snippets and sophisticated convolutional neural networks to tackle real-world problems in medical image analysis and beyond. Features: Provides programming guidance for creation of sophisticated and reliable neural networks for image processing. Incorporates the comparative study on GAN, stable diffusion, and its application on medical image data augmentation. Focuses on solving real-world medical imaging problems. Discusses advanced concepts of deep learning along with the latest technology such as GPT, stable diffusion, and ViT. Develops applicable knowledge of deep learning using Python programming, followed by code snippets and OOP concepts. This book is aimed at graduate students and researchers in medical data analytics, medical image analysis, signal processing, and deep learning.
Deep Learning For Coders With Fastai And Pytorch
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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29
Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
A Beginner S Guide To Introduce Artificial Intelligence In Teaching And Learning
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Author : Muralidhar Kurni
language : en
Publisher: Springer Nature
Release Date : 2023-06-28
A Beginner S Guide To Introduce Artificial Intelligence In Teaching And Learning written by Muralidhar Kurni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-28 with Education categories.
This book reimagines education in today’s Artificial Intelligence (AI) world and the Fourth Industrial Revolution. Artificial intelligence will drastically affect every industry and sector, and education is no exception. This book aims at how AI may impact the teaching and learning process in education. This book is designed to demystify AI for teachers and learners. This book will help improve education and support institutions in the phenomena of the emergence of AI in teaching and learning. This book presents a comprehensive study of how AI improves teaching and learning, from AI-based learning platforms to AI-assisted proctored examinations. This book provides educators, learners, and administrators on how AI makes sense in their everyday practice. Describing the application of AI in ten key aspects, this comprehensive volume prepares educational leaders, designers, researchers, and policymakers to effectively rethink the teaching and learning process and environments that students need to thrive. The readers of this book never fall behind the fast pace and promising innovations of today’s most advanced learning technology.
Introduction To Machine Learning
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Author : Ethem Alpaydin
language : en
Publisher: MIT Press
Release Date : 2014-08-22
Introduction To Machine Learning written by Ethem Alpaydin and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-22 with Computers categories.
Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
Practical Guide To Simulation In Delivery Room Emergencies
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Author : Gilda Cinnella
language : en
Publisher: Springer Nature
Release Date : 2023-06-13
Practical Guide To Simulation In Delivery Room Emergencies written by Gilda Cinnella and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-13 with Medical categories.
In this book the use of hybrid simulation in delivery room emergencies is described and shown. The use of a patient actor combined with a task trainer within the same session substantially improve the training for practical management of intrapartum emergencies in real life, reducing the risk of failure of operative vaginal delivery and of related adverse events, including perinatal or maternal complications. Furthermore, simulation with high reality computerized mannequin and scenography of emergency situation can improve technical and manual skills of the participants. For this book and the related videos, a new generation of mannequins suitable for both clinical manoeuvres and ultrasound examination is used to simulate all clinical scenarios of emergency that can happen in the delivery room for both the mother and the child. This unique book is a useful tool for medical students, residents, practicing pediatricians, anesthetists, obstetricians and all health care professionals working in the delivery room in their ability to deal with critical and emergency situations with safety and good medical practice.
Python Programming Deep Learning
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Author : Anthony Adams
language : en
Publisher: Anthony Adams
Release Date : 2021-12-17
Python Programming Deep Learning written by Anthony Adams and has been published by Anthony Adams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-17 with Computers categories.
Easily Boost Your Skills In Python Programming & Become A Master In Deep Learning & Data Analysis! 💻 Python is an interpreted, high-level, general-purpose programming language that emphasizes code readability with its notable use of significant whitespace. What makes Python so popular in the IT industry is that it uses an object-oriented approach, which enables programmers to write clear, logical code for all types of projects, whether big or small. Hone your Python Programming skills and gain a sharp edge over other programmers the EASIEST way possible... with this practical beginner’s guide! In his 3-in-1 Python crash course for beginners, Anthony Adams gives novices like you simple, yet efficient tips and tricks to become a MASTER in Python coding for artificial intelligence, neural networks, machine learning, and data science/analysis! Here’s what you’ll get: ✅ Highly innovative ways to boost your understanding of Python programming, data analysis, and machine learning ✅ Quickly and effectively stop fraud with machine learning ✅ Practical and efficient exercises that make understanding Python quick & easy And so much more! As a beginner, you might feel a bit intimidated by the complexities of coding. Add the fact that most Python Programming crash course guides make learning harder than it has to be! ✓ With the help of this 3-in-1 guide, you will be given carefully sequenced Python Programming lessons that’ll maximize your understanding, and equip you with all the skills for real-life application! ★ Thrive in the IT industry with this comprehensive Python Programming crash course! ★ Scroll up, Click on “Buy Now”, and Start Learning Today!
Ict Analysis And Applications
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Author : Simon Fong
language : en
Publisher: Springer Nature
Release Date : 2022-01-07
Ict Analysis And Applications written by Simon Fong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-07 with Technology & Engineering categories.
This book proposes new technologies and discusses future solutions for ICT design infrastructures, as reflected in high-quality papers presented at the 6th International Conference on ICT for Sustainable Development (ICT4SD 2021), held in Goa, India, on 5–6 August 2021. The book covers the topics such as big data and data mining, data fusion, IoT programming toolkits and frameworks, green communication systems and network, use of ICT in smart cities, sensor networks and embedded system, network and information security, wireless and optical networks, security, trust, and privacy, routing and control protocols, cognitive radio and networks, and natural language processing. Bringing together experts from different countries, the book explores a range of central issues from an international perspective.
Intelligent Computing Techniques In Biomedical Imaging
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Author : Bikesh Kumar Singh
language : en
Publisher: Elsevier
Release Date : 2024-08-23
Intelligent Computing Techniques In Biomedical Imaging written by Bikesh Kumar Singh and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-23 with Science categories.
Intelligent Computing Techniques in Biomedical Imaging provides comprehensive and state-of-the-art applications of Computational Intelligence techniques used in biomedical image analysis for disease detection and diagnosis. The book offers readers a stepwise approach from fundamental to advanced techniques using real-life medical examples and tutorials. The editors have divided the book into five sections, from prerequisites to case studies.Section I presents the prerequisites, where the reader will find fundamental concepts needed for advanced topics covered later in this book. This primarily includes a thorough introduction to Artificial Intelligence, probability theory and statistical learning. The second section covers Computational Intelligence methods for medical image acquisition and pre-processing for biomedical images. In this section, readers will find AI applied to conventional and advanced biomedical imaging modalities such as X-rays, CT scan, MRI, Mammography, Ultrasound, MR Spectroscopy, Positron Emission Tomography (PET), Ultrasound Elastography, Optical Coherence Tomography (OCT), Functional MRI, Hybrid Modalities, as well as pre-processing topics such as medical image enhancement, segmentation, and compression. Section III covers description and representation of medical images. Here the reader will find various categories of features and their relevance in different medical imaging tasks. This section also discusses feature selection techniques based on filter method, wrapper method, embedded method, and more.The fourth section covers Computational Intelligence techniques used for medical image classification, including Artificial Neural Networks, Support Vector Machines, Decision Trees, Nearest Neighbor Classifiers, Random Forest, clustering, extreme learning, Convolution Neural Networks (CNN), and Recurrent Neural Networks. This section also includes a discussion of computer aided diagnosis and performance evaluation in radiology.The final section of Intelligent Computing Techniques in Biomedical Imaging provides readers with a wealth of real-world Case Studies for Computational Intelligence techniques in applications such as neuro-developmental disorders, brain tumor detection, breast cancer detection, bone fracture detection, pulmonary imaging, thyroid disorders, imaging technologies in dentistry, diagnosis of ocular diseases, cardiovascular imaging, and multimodal imaging. - Introduces Fourier theory and signal analysis tailored to applications in optical communications devices and systems - Provides strong theoretical background, making it a ready resource for researchers and advanced students in optical communication and optical signal processing - Starts from basic theory and then develops descriptions of useful applications
Deep Learning For Medical Image Analysis
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2017-01-18
Deep Learning For Medical Image Analysis written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-18 with Computers categories.
Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache