Biomedical Computing For Breast Cancer Detection And Diagnosis

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Biomedical Computing for Breast Cancer Detection and Diagnosis

Pinheiro dos Santos, Wellington,Azevedo da Silva, Washington Wagner,de Santana, Maira Araujo
Biomedical Computing for Breast Cancer Detection and Diagnosis Book PDF

Author : Pinheiro dos Santos, Wellington,Azevedo da Silva, Washington Wagner,de Santana, Maira Araujo
Publisher : IGI Global
Page : 357 pages
File Size : 50,7 Mb
Release : 2020-07-17
Category : Medical
ISBN : 9781799834571

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Biomedical Computing for Breast Cancer Detection and Diagnosis by Pinheiro dos Santos, Wellington,Azevedo da Silva, Washington Wagner,de Santana, Maira Araujo Pdf

Despite success with treatment when diagnosed early, breast cancer is still one of the most fatal forms of cancer for women. Imaging diagnosis is still one of the most efficient ways to detect early breast changes with mammography among the most used techniques. However, there are other techniques that have emerged as alternatives or even complementary tests in the early detection of breast lesions (e.g., breast thermography and electrical impedance tomography). Artificial intelligence can be used to optimize image diagnosis, increasing the reliability of the reports and supporting professionals who do not have enough knowledge or experience to make good diagnoses. Biomedical Computing for Breast Cancer Detection and Diagnosis is a collection of research that presents a review of the physiology and anatomy of the breast; the dynamics of breast cancer; principles of pattern recognition, artificial neural networks, and computer graphics; and the breast imaging techniques and computational methods to support and optimize the diagnosis. While highlighting topics including mammograms, thermographic imaging, and intelligent systems, this book is ideally designed for medical oncologists, surgeons, biomedical engineers, medical imaging professionals, cancer researchers, academicians, and students in medicine, biomedicine, biomedical engineering, and computer science.

Next Generation Point-of-care Biomedical Sensors Technologies for Cancer Diagnosis

Pranjal Chandra,Yen Nee Tan,Surinder P. Singh
Next Generation Point of care Biomedical Sensors Technologies for Cancer Diagnosis Book PDF

Author : Pranjal Chandra,Yen Nee Tan,Surinder P. Singh
Publisher : Springer
Page : 396 pages
File Size : 43,5 Mb
Release : 2017-12-30
Category : Medical
ISBN : 9789811047268

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Next Generation Point-of-care Biomedical Sensors Technologies for Cancer Diagnosis by Pranjal Chandra,Yen Nee Tan,Surinder P. Singh Pdf

This book presents recent research on cancer detection methods based on nanobiosensors, which offer ultrasensitive point-of-care diagnosis. Several methods for diagnosing cancer have been discovered and many more are currently being developed. Conventional clinical approaches to detecting cancers are based on a biopsy followed by histopathology, or on the use of biomarkers (protein levels or nucleic acid content). Biopsy is the most widely used technique; however, it is an invasive technique and is not always applicable. Furthermore, biomarker-based detection cannot be relied on when the biomarkers are present in an extremely low concentration in the body fluids and in malignant tissues. Thus, in recent years highly sensitive and robust new cancer diagnosis techniques have been developed for clinical application, and may offer an alternative strategy for cancer diagnosis. As such, this book gathers the latest point-of-care cancer diagnostic methods and protocols based on biomedical sensors, microfluidics, and integrated systems engineering. It also discusses recent developments and diagnostics tests that can be conducted outside the laboratory in remote areas. These technologies include electrochemical sensors, paper-based microfluidics, and other kit-based diagnostic methods that can be adapted to bring cancer detection and diagnostics to more remote settings around the globe. Overall, the book provides students, researchers, and clinicians alike a comprehensive overview of interdisciplinary approaches to cancer diagnosis.

Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer

Paola Casti,Arianna Mencattini,Marcello Salmeri,Rangaraj M. Rangayyan
Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer Book PDF

Author : Paola Casti,Arianna Mencattini,Marcello Salmeri,Rangaraj M. Rangayyan
Publisher : Morgan & Claypool Publishers
Page : 188 pages
File Size : 41,7 Mb
Release : 2017-07-06
Category : Technology & Engineering
ISBN : 9781681731575

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Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer by Paola Casti,Arianna Mencattini,Marcello Salmeri,Rangaraj M. Rangayyan Pdf

The identification and interpretation of the signs of breast cancer in mammographic images from screening programs can be very difficult due to the subtle and diversified appearance of breast disease. This book presents new image processing and pattern recognition techniques for computer-aided detection and diagnosis of breast cancer in its various forms. The main goals are: (1) the identification of bilateral asymmetry as an early sign of breast disease which is not detectable by other existing approaches; and (2) the detection and classification of masses and regions of architectural distortion, as benign lesions or malignant tumors, in a unified framework that does not require accurate extraction of the contours of the lesions. The innovative aspects of the work include the design and validation of landmarking algorithms, automatic Tabár masking procedures, and various feature descriptors for quantification of similarity and for contour independent classification of mammographic lesions. Characterization of breast tissue patterns is achieved by means of multidirectional Gabor filters. For the classification tasks, pattern recognition strategies, including Fisher linear discriminant analysis, Bayesian classifiers, support vector machines, and neural networks are applied using automatic selection of features and cross-validation techniques. Computer-aided detection of bilateral asymmetry resulted in accuracy up to 0.94, with sensitivity and specificity of 1 and 0.88, respectively. Computer-aided diagnosis of automatically detected lesions provided sensitivity of detection of malignant tumors in the range of [0.70, 0.81] at a range of falsely detected tumors of [0.82, 3.47] per image. The techniques presented in this work are effective in detecting and characterizing various mammographic signs of breast disease.

Human Cancer Diagnosis and Detection Using Exascale Computing

Kapil Joshi,Somil Kumar Gupta
Human Cancer Diagnosis and Detection Using Exascale Computing Book PDF

Author : Kapil Joshi,Somil Kumar Gupta
Publisher : John Wiley & Sons
Page : 340 pages
File Size : 53,8 Mb
Release : 2024-04-02
Category : Medical
ISBN : 9781394197675

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Human Cancer Diagnosis and Detection Using Exascale Computing by Kapil Joshi,Somil Kumar Gupta Pdf

Human Cancer Diagnosis and Detection Using Exascale Computing The book provides an in-depth exploration of how high-performance computing, particularly exascale computing, can be used to revolutionize cancer diagnosis and detection; it also serves as a bridge between the worlds of computational science and clinical oncology. Exascale computing has the potential to increase our ability in terms of computation to develop efficient methods for a better healthcare system. This technology promises to revolutionize cancer diagnosis and detection, ushering in an era of unprecedented precision, speed, and efficiency. The fusion of exascale computing with the field of oncology has the potential to redefine the boundaries of what is possible in the fight against cancer. The book is a comprehensive exploration of this transformative unification of science, medicine, and technology. It delves deeply into the realm of exascale computing and its profound implications for cancer research and patient care. The 18 chapters are authored by experts from diverse fields who have dedicated their careers to pushing the boundaries of what is achievable in the realm of cancer diagnosis and detection. The chapters cover a wide range of topics, from the fundamentals of exascale computing and its application to cancer genomics to the development of advanced imaging techniques and machine learning algorithms. Explored is the integration of data analytics, artificial intelligence, and high-performance computing to move cancer research to the next phase and support the creation of novel medical tools and technology for the detection and diagnosis of cancer. Audience This book has a wide audience from both computer sciences (information technology, computer vision, artificial intelligence, software engineering, applied mathematics) and the medical field (biomedical engineering, bioinformatics, oncology). Researchers, practitioners and students will find this groundbreaking book novel and very useful.

Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management

R. N. G. Naguib,G. V. Sherbet
Artificial Neural Networks in Cancer Diagnosis Prognosis and Patient Management Book PDF

Author : R. N. G. Naguib,G. V. Sherbet
Publisher : CRC Press
Page : 216 pages
File Size : 41,8 Mb
Release : 2001-06-22
Category : Medical
ISBN : 9781420036381

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Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management by R. N. G. Naguib,G. V. Sherbet Pdf

The potential value of artificial neural networks (ANN) as a predictor of malignancy has begun to receive increased recognition. Research and case studies can be found scattered throughout a multitude of journals. Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management brings together the work of top researchers - primaril

Computer-aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer

Shantanu Banik,Rangaraj Rangayyan,J.E. Leo Desautels
Computer aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer Book PDF

Author : Shantanu Banik,Rangaraj Rangayyan,J.E. Leo Desautels
Publisher : Morgan & Claypool Publishers
Page : 195 pages
File Size : 51,7 Mb
Release : 2013-01-01
Category : Technology & Engineering
ISBN : 9781627050838

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Computer-aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer by Shantanu Banik,Rangaraj Rangayyan,J.E. Leo Desautels Pdf

Architectural distortion is an important and early sign of breast cancer, but because of its subtlety, it is a common cause of false-negative findings on screening mammograms. Screening mammograms obtained prior to the detection of cancer could contain subtle signs of early stages of breast cancer, in particular, architectural distortion. This book presents image processing and pattern recognition techniques to detect architectural distortion in prior mammograms of interval-cancer cases. The methods are based upon Gabor filters, phase portrait analysis, procedures for the analysis of the angular spread of power, fractal analysis, Laws' texture energy measures derived from geometrically transformed regions of interest (ROIs), and Haralick's texture features. With Gabor filters and phase-portrait analysis, 4,224 ROIs were automatically obtained from 106 prior mammograms of 56 interval-cancer cases, including 301 true-positive ROIs related to architectural distortion, and from 52 mammograms of 13 normal cases. For each ROI, the fractal dimension, the entropy of the angular spread of power, 10 Laws' texture energy measures, and Haralick's 14 texture features were computed. The areas under the receiver operating characteristic (ROC) curves obtained using the features selected by stepwise logistic regression and the leave-one-image-out method are 0.77 with the Bayesian classifier, 0.76 with Fisher linear discriminant analysis, and 0.79 with a neural network classifier. Free-response ROC analysis indicated sensitivities of 0.80 and 0.90 at 5.7 and 8.8 false positives (FPs) per image, respectively, with the Bayesian classifier and the leave-one-image-out method. The present study has demonstrated the ability to detect early signs of breast cancer 15 months ahead of the time of clinical diagnosis, on the average, for interval-cancer cases, with a sensitivity of 0.8 at 5.7 FP/image. The presented computer-aided detection techniques, dedicated to accurate detection and localization of architectural distortion, could lead to efficient detection of early and subtle signs of breast cancer at pre-mass-formation stages. Table of Contents: Introduction / Detection of Early Signs of Breast Cancer / Detection and Analysis of Oriented Patterns / Detection of Potential Sites of Architectural Distortion / Experimental Set Up and Datasets / Feature Selection and Pattern Classification / Analysis of Oriented Patterns Related to Architectural Distortion / Detection of Architectural Distortion in Prior Mammograms / Concluding Remarks

Mammography and Beyond

National Research Council,Division on Earth and Life Studies,Institute of Medicine,National Cancer Policy Board,Committee on Technologies for the Early Detection of Breast Cancer
Mammography and Beyond Book PDF

Author : National Research Council,Division on Earth and Life Studies,Institute of Medicine,National Cancer Policy Board,Committee on Technologies for the Early Detection of Breast Cancer
Publisher : National Academies Press
Page : 312 pages
File Size : 51,7 Mb
Release : 2001-07-23
Category : Medical
ISBN : 0309171318

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Mammography and Beyond by National Research Council,Division on Earth and Life Studies,Institute of Medicine,National Cancer Policy Board,Committee on Technologies for the Early Detection of Breast Cancer Pdf

Each year more than 180,000 new cases of breast cancer are diagnosed in women in the U.S. If cancer is detected when small and local, treatment options are less dangerous, intrusive, and costly-and more likely to lead to a cure. Yet those simple facts belie the complexity of developing and disseminating acceptable techniques for breast cancer diagnosis. Even the most exciting new technologies remain clouded with uncertainty. Mammography and Beyond provides a comprehensive and up-to-date perspective on the state of breast cancer screening and diagnosis and recommends steps for developing the most reliable breast cancer detection methods possible. This book reviews the dramatic expansion of breast cancer awareness and screening, examining the capabilities and limitations of current and emerging technologies for breast cancer detection and their effectiveness at actually reducing deaths. The committee discusses issues including national policy toward breast cancer detection, roles of public and private agencies, problems in determining the success of a technique, availability of detection methods to specific populations of women, women's experience during the detection process, cost-benefit analyses, and more. Examining current practices and specifying research and other needs, Mammography and Beyond will be an indispensable resource to policy makers, public health officials, medical practitioners, researchers, women's health advocates, and concerned women and their families.

Modeling and Analysis of Shape with Applications in Computer-aided Diagnosis of Breast Cancer

Denise Guliato,Rangaraj Rangayyan
Modeling and Analysis of Shape with Applications in Computer aided Diagnosis of Breast Cancer Book PDF

Author : Denise Guliato,Rangaraj Rangayyan
Publisher : Springer Nature
Page : 75 pages
File Size : 41,6 Mb
Release : 2022-05-31
Category : Technology & Engineering
ISBN : 9783031794292

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Modeling and Analysis of Shape with Applications in Computer-aided Diagnosis of Breast Cancer by Denise Guliato,Rangaraj Rangayyan Pdf

Malignant tumors due to breast cancer and masses due to benign disease appear in mammograms with different shape characteristics: the former usually have rough, spiculated, or microlobulated contours, whereas the latter commonly have smooth, round, oval, or macrolobulated contours. Features that characterize shape roughness and complexity can assist in distinguishing between malignant tumors and benign masses. In spite of the established importance of shape factors in the analysis of breast tumors and masses, difficulties exist in obtaining accurate and artifact-free boundaries of the related regions from mammograms. Whereas manually drawn contours could contain artifacts related to hand tremor and are subject to intra-observer and inter-observer variations, automatically detected contours could contain noise and inaccuracies due to limitations or errors in the procedures for the detection and segmentation of the related regions. Modeling procedures are desired to eliminate the artifacts in a given contour, while preserving the important and significant details present in the contour. This book presents polygonal modeling methods that reduce the influence of noise and artifacts while preserving the diagnostically relevant features, in particular the spicules and lobulations in the given contours. In order to facilitate the derivation of features that capture the characteristics of shape roughness of contours of breast masses, methods to derive a signature based on the turning angle function obtained from the polygonal model are described. Methods are also described to derive an index of spiculation, an index characterizing the presence of convex regions, an index characterizing the presence of concave regions, an index of convexity, and a measure of fractal dimension from the turning angle function. Results of testing the methods with a set of 111 contours of 65 benign masses and 46 malignant tumors are presented and discussed. It is shown that shape modeling and analysis can lead to classification accuracy in discriminating between benign masses and malignant tumors, in terms of the area under the receiver operating characteristic curve, of up to 0.94. The methods have applications in modeling and analysis of the shape of various types of regions or objects in images, computer vision, computer graphics, and analysis of biomedical images, with particular significance in computer-aided diagnosis of breast cancer. Table of Contents: Analysis of Shape / Polygonal Modeling of Contours / Shape Factors for Pattern Classification / Classification of Breast Masses

Artificial Intelligence in Breast Cancer Early Detection and Diagnosis

Khalid Shaikh,Sabitha Krishnan,Rohit Thanki
Artificial Intelligence in Breast Cancer Early Detection and Diagnosis Book PDF

Author : Khalid Shaikh,Sabitha Krishnan,Rohit Thanki
Publisher : Springer Nature
Page : 107 pages
File Size : 44,6 Mb
Release : 2020-12-04
Category : Technology & Engineering
ISBN : 9783030592080

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Artificial Intelligence in Breast Cancer Early Detection and Diagnosis by Khalid Shaikh,Sabitha Krishnan,Rohit Thanki Pdf

This book provides an introduction to next generation smart screening technology for medical image analysis that combines artificial intelligence (AI) techniques with digital screening to develop innovative methods for detecting breast cancer. The authors begin with a discussion of breast cancer, its characteristics and symptoms, and the importance of early screening.They then provide insight on the role of artificial intelligence in global healthcare, screening methods for breast cancer using mammogram, ultrasound, and thermogram images, and the potential benefits of using AI-based systems for clinical screening to more accurately detect, diagnose, and treat breast cancer. Discusses various existing screening methods for breast cancer Presents deep information on artificial intelligence-based screening methods Discusses cancer treatment based on geographical differences and cultural characteristics

Artificial Intelligence Techniques in Breast Cancer Diagnosis and Prognosis

Ashlesha Jain,Ajita Jain,Sandhya Jain,Lakhmi Jain
Artificial Intelligence Techniques in Breast Cancer Diagnosis and Prognosis Book PDF

Author : Ashlesha Jain,Ajita Jain,Sandhya Jain,Lakhmi Jain
Publisher : World Scientific
Page : 348 pages
File Size : 51,5 Mb
Release : 2000-08-21
Category : Computers
ISBN : 9789814492676

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Artificial Intelligence Techniques in Breast Cancer Diagnosis and Prognosis by Ashlesha Jain,Ajita Jain,Sandhya Jain,Lakhmi Jain Pdf

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. Contents:An Introduction to Breast Cancer Diagnosis, Prognosis, and Artificial Intelligence (N Harbeck et al.)Automatic Image Feature Extraction for Diagnosis and Prognosis of Breast Cancer (M J Bottema et al.)Decision Support in Breast Cancer: Recent Advances in Prognostic and Predictive Techniques (R Kates et al.)MammoNet: A Bayesian Network Diagnosing Breast Cancer (L M Roberts)Predicting Prognosis and Treatment Response in Breast Cancer Patients (M G Daidone & D Coradini)Computer-Aided Breast Cancer Diagnosis (H-P Chan et al.)Which Decision Support Technologies are Appropriate for the Cytodiagnosis of Breast Cancer? (S S Cross et al.)Xcyt: A System for Remote Cytological Diagnosis and Prognosis of Breast Cancer (W N Street) Readership: Medical practitioners, researchers and graduate students. Keywords:Artificial Intelligence;Soft Computing;Breast Cancer;Diagnosis;Prognosis;Fuzzy Systems;Neural NetworksReviews:“The editors have done an excellent job of putting together a book that highlights the advances and controversies that surround the subject … The book will be of particular interest to clinical decision support systems designers and academic oncologists.”Cancer Forum

Computational Intelligence in Cancer Diagnosis

Janmenjoy Nayak,Danilo Pelusi,Bighnaraj Naik,Mishra Manohar,Khan Muhammad,David Al-Dabass
Computational Intelligence in Cancer Diagnosis Book PDF

Author : Janmenjoy Nayak,Danilo Pelusi,Bighnaraj Naik,Mishra Manohar,Khan Muhammad,David Al-Dabass
Publisher : Academic Press
Page : 422 pages
File Size : 40,7 Mb
Release : 2023-04-12
Category : Science
ISBN : 9780323903530

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Computational Intelligence in Cancer Diagnosis by Janmenjoy Nayak,Danilo Pelusi,Bighnaraj Naik,Mishra Manohar,Khan Muhammad,David Al-Dabass Pdf

Computational Intelligence in Cancer Diagnosis: Progress and Challenges provides insights into the current strength and weaknesses of different applications and research findings on computational intelligence in cancer research. The book improves the exchange of ideas and coherence among various computational intelligence methods and enhances the relevance and exploitation of application areas for both experienced and novice end-users. Topics discussed include neural networks, fuzzy logic, connectionist systems, genetic algorithms, evolutionary computation, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. The book's chapters are written by international experts from both cancer research, oncology and computational sides to cover different aspects and make it comprehensible for readers with no background on informatics. Contains updated information about advanced computational intelligence, spanning the areas of neural networks, fuzzy logic, connectionist systems, genetic algorithms, evolutionary computation, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems in diagnosing cancer diseases Discusses several cancer types, including their detection, treatment and prevention Presents case studies that illustrate the applications of intelligent computing in data analysis to help readers to analyze and advance their research in cancer

Computational Analysis and Deep Learning for Medical Care

Amit Kumar Tyagi
Computational Analysis and Deep Learning for Medical Care Book PDF

Author : Amit Kumar Tyagi
Publisher : John Wiley & Sons
Page : 532 pages
File Size : 50,7 Mb
Release : 2021-08-24
Category : Computers
ISBN : 9781119785729

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Computational Analysis and Deep Learning for Medical Care by Amit Kumar Tyagi Pdf

The book details deep learning models like ANN, RNN, LSTM, in many industrial sectors such as transportation, healthcare, military, agriculture, with valid and effective results, which will help researchers find solutions to their deep learning research problems. We have entered the era of smart world devices, where robots or machines are being used in most applications to solve real-world problems. These smart machines/devices reduce the burden on doctors, which in turn make their lives easier and the lives of their patients better, thereby increasing patient longevity, which is the ultimate goal of computer vision. Therefore, the goal in writing this book is to attempt to provide complete information on reliable deep learning models required for e-healthcare applications. Ways in which deep learning can enhance healthcare images or text data for making useful decisions are discussed. Also presented are reliable deep learning models, such as neural networks, convolutional neural networks, backpropagation, and recurrent neural networks, which are increasingly being used in medical image processing, including for colorization of black and white X-ray images, automatic machine translation images, object classification in photographs/images (CT scans), character or useful generation (ECG), image caption generation, etc. Hence, reliable deep learning methods for the perception or production of better results are a necessity for highly effective e-healthcare applications. Currently, the most difficult data-related problem that needs to be solved concerns the rapid increase of data occurring each day via billions of smart devices. To address the growing amount of data in healthcare applications, challenges such as not having standard tools, efficient algorithms, and a sufficient number of skilled data scientists need to be overcome. Hence, there is growing interest in investigating deep learning models and their use in e-healthcare applications. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in transportation, healthcare, biomedicine, military, agriculture.

AI in Biological and Biomedical Imaging

Xin Gao,Lihua Li,Min Xu
AI in Biological and Biomedical Imaging Book PDF

Author : Xin Gao,Lihua Li,Min Xu
Publisher : Frontiers Media SA
Page : 161 pages
File Size : 44,9 Mb
Release : 2022-01-17
Category : Science
ISBN : 9782889740499

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AI in Biological and Biomedical Imaging by Xin Gao,Lihua Li,Min Xu Pdf

Doctors Gao and Li hold patents related to artificial intelligence.

Bioinformatics and Biomedical Engineering

Ignacio Rojas,Olga Valenzuela,Fernando Rojas,Luis Javier Herrera,Francisco Ortuño
Bioinformatics and Biomedical Engineering Book PDF

Author : Ignacio Rojas,Olga Valenzuela,Fernando Rojas,Luis Javier Herrera,Francisco Ortuño
Publisher : Springer Nature
Page : 843 pages
File Size : 51,5 Mb
Release : 2020-04-30
Category : Science
ISBN : 9783030453855

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Bioinformatics and Biomedical Engineering by Ignacio Rojas,Olga Valenzuela,Fernando Rojas,Luis Javier Herrera,Francisco Ortuño Pdf

This volume constitutes the proceedings of the 8th International Work-Conference on IWBBIO 2020, held in Granada, Spain, in May 2020. The total of 73papers presented in the proceedings, was carefully reviewed and selected from 241 submissions. The papers are organized in topical sections as follows: Biomarker Identification; Biomedical Engineering; Biomedical Signal Analysis; Bio-Nanotechnology; Computational Approaches for Drug Design and Personalized Medicine; Computational Proteomics and Protein-Protein Interactions; Data Mining from UV/VIS/NIR Imaging and Spectrophotometry; E-Health Technology, Services and Applications; Evolving Towards Digital Twins in Healthcare (EDITH); High Performance in Bioinformatics; High-Throughput Genomics: Bioinformatic Tools and Medical Applications; Machine Learning in Bioinformatics; Medical Image Processing; Simulation and Visualization of Biological Systems.

Saving Women's Lives

National Research Council,Institute of Medicine,National Cancer Policy Board,Committee on New Approaches to Early Detection and Diagnosis of Breast Cancer
Saving Women s Lives Book PDF

Author : National Research Council,Institute of Medicine,National Cancer Policy Board,Committee on New Approaches to Early Detection and Diagnosis of Breast Cancer
Publisher : National Academies Press
Page : 144 pages
File Size : 52,7 Mb
Release : 2004-12-18
Category : Medical
ISBN : 9780309094382

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Saving Women's Lives by National Research Council,Institute of Medicine,National Cancer Policy Board,Committee on New Approaches to Early Detection and Diagnosis of Breast Cancer Pdf

In this report The Breast Cancer Research Foundation (BCRF) and the Institute of Medicine (IOM) present a one-day symposium that was held at the IOM to further disseminate the conclusions and recommendations of the joint IOM and National Research Council report, Saving Women's Lives: Strategies for Improving Breast Cancer Detection and Diagnosis. The committee assembled for this event was asked to share insights and consider ways in which the objectives of the report could be achieved from the standpoint of what women need to know, the best models of screening programs, manpower, risk stratification, basic research, and payment. This symposium seeks to provide continuing food for thought and ideas for actions in support of breast cancer detection and diagnosis and saving women's lives.