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Artificial Intelligence in Medicine

Artificial Intelligence in Medicine PDF Author: David Riaño
Publisher: Springer
ISBN: 303021642X
Category : Computers
Languages : en
Pages : 431

Book Description
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine PDF Author: David Riaño
Publisher: Springer
ISBN: 303021642X
Category : Computers
Languages : en
Pages : 431

Book Description
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Deep Learning for the Life Sciences

Deep Learning for the Life Sciences PDF Author: Bharath Ramsundar
Publisher: O'Reilly Media
ISBN: 1492039802
Category : Science
Languages : en
Pages : 236

Book Description
Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working

An efficient classification framework for breast cancer using hyper parameter tuned Random Decision Forest Classifier and Bayesian Optimization

An efficient classification framework for breast cancer using hyper parameter tuned Random Decision Forest Classifier and Bayesian Optimization PDF Author: Pratheep Kumar
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 11

Book Description
Decision tree algorithm is one of the algorithm which is easily understandable and interpretable algorithm used in both training and application purpose during breast cancer prognosis. To address this problem, Random Decision Forests are proposed. In this manuscript, the breast cancer classification can be determined by combining the advantages of Feature Weight and Hyper Parameter Tuned Random Decision Forest classifier

Artificial Intelligence Techniques In Breast Cancer Diagnosis And Prognosis

Artificial Intelligence Techniques In Breast Cancer Diagnosis And Prognosis PDF Author: Lakhmi C Jain
Publisher: World Scientific
ISBN: 9814492671
Category : Computers
Languages : en
Pages : 350

Book Description
The main aim of this book is to present a sample of recent research on the application of novel artificial intelligence paradigms to the diagnosis and prognosis of breast cancer. These paradigms include neural networks, fuzzy logic and evolutionary computing. Artificial intelligence techniques offer advantages — such as adaptation, fault tolerance, learning and human-like behavior — over conventional computing techniques. The idea is to combine the pathological, intelligent and statistical approaches to enable simple and accurate diagnosis and prognosis.This book is the first of its kind on the topic of artificial intelligence in breast cancer. It presents the applications of artificial intelligence in breast cancer diagnosis and prognosis, and includes state-of-the-art concepts in the field. It contains contributions from Australia, Germany, Italy, UK and the USA.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging PDF Author: Erik R. Ranschaert
Publisher: Springer
ISBN: 3319948784
Category : Medical
Languages : en
Pages : 369

Book Description
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Breast Cancer Screening and Diagnosis

Breast Cancer Screening and Diagnosis PDF Author: Mahesh K Shetty
Publisher: Springer
ISBN: 1493912674
Category : Medical
Languages : en
Pages : 464

Book Description
This book presents the current trends and practices in breast imaging. Topics include mammographic interpretation; breast ultrasound; breast MRI; management of the symptomatic breast in young, pregnant and lactating women; breast intervention with imaging pathological correlation; the postoperative breast and current and emerging technologies in breast imaging. It emphasizes the importance of fostering a multidisciplinary approach in the diagnosis and treatment of breast diseases. Featuring more than 800 high-resolution images and showcasing contributions from leading authorities in the screening, diagnosis and management of the breast cancer patient, Breast Cancer Screening and Diagnosis is a valuable resource for radiologists, oncologists and surgeons.

Digital Breast Tomosynthesis

Digital Breast Tomosynthesis PDF Author: Alberto Tagliafico
Publisher: Springer
ISBN: 3319286315
Category : Medical
Languages : en
Pages : 156

Book Description
This book provides a comprehensive description of the screening and clinical applications of digital breast tomosynthesis (DBT) and offers straightforward, clear guidance on use of the technique. Informative clinical cases are presented to illustrate how to take advantage of DBT in clinical practice. The importance of DBT as a diagnostic tool for both screening and diagnosis is increasing rapidly. DBT improves upon mammography by depicting breast tissue on a video clip made of cross‐sectional images reconstructed in correspondence with their mammographic planes of acquisition. DBT results in markedly reduced summation of overlapping breast tissue and offers the potential to improve mammographic breast cancer surveillance and diagnosis. This book will be an excellent practical teaching guide for beginners and a useful reference for more experienced radiologists.

CMBEBIH 2017

CMBEBIH 2017 PDF Author: Almir Badnjevic
Publisher: Springer
ISBN: 9811041660
Category : Technology & Engineering
Languages : en
Pages : 806

Book Description
This volume presents the proceedings of the International Conference on Medical and Biological Engineering held from 16 to 18 March 2017 in Sarajevo, Bosnia and Herzegovina. Focusing on the theme of ‘Pursuing innovation. Shaping the future’, it highlights the latest advancements in Biomedical Engineering and also presents the latest findings, innovative solutions and emerging challenges in this field. Topics include: - Biomedical Signal Processing - Biomedical Imaging and Image Processing - Biosensors and Bioinstrumentation - Bio-Micro/Nano Technologies - Biomaterials - Biomechanics, Robotics and Minimally Invasive Surgery - Cardiovascular, Respiratory and Endocrine Systems Engineering - Neural and Rehabilitation Engineering - Molecular, Cellular and Tissue Engineering - Bioinformatics and Computational Biology - Clinical Engineering and Health Technology Assessment - Health Informatics, E-Health and Telemedicine - Biomedical Engineering Education - Pharmaceutical Engineering

Data Analytics in Bioinformatics

Data Analytics in Bioinformatics PDF Author: Rabinarayan Satpathy
Publisher: John Wiley & Sons
ISBN: 111978560X
Category : Computers
Languages : en
Pages : 433

Book Description
Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems

Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems PDF Author: E. Priya
Publisher: Springer Nature
ISBN: 9811561419
Category : Medical
Languages : en
Pages : 290

Book Description
This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.