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Author: Priyanka Vaidya Publisher: ISBN: Category : Bioinformatics Languages : en Pages : 107
Book Description
"Breast cancer is the second most common form of cancer amongst females and also the fifth most cause of cancer deaths worthwide. In case of this particular type of malignancy, early detection is the best form of cure and hence timely and accurate diagnosis of the tumor is extremely vital. Extensive research has been carried out on automating the critical diagnosis procedure as various machine learning algorithms and software tools have been deployed to aid physicians in optimizing the decision task effectively. In this research, we present a novel matrix of an artificial neural network system to effectively classify breast cancer tumors as either malignant or benign. This classification system makes use of both clinical as well as genetic data. Artificial neural networks of different architectures are incorporated in the system to classify both the image based clinical dataset as well as the microarray dataset derived from blood cells. Both the datasets are subjected to indificual analysis to compute the optimum number of input features to the neural network matrix. Randomly selected sample instances from both the clinical and microarray original datasets then serve as an input to the Dempster-Shafer theory of evidence block where the outputs are fused to provide a final diagnostic assessment and compared with the neural network analysis. The results indicate that the fused output of the Dempster-Shafer block significantly outperform the individual classifier's outputs."--Abstract.
Author: Priyanka Vaidya Publisher: ISBN: Category : Bioinformatics Languages : en Pages : 107
Book Description
"Breast cancer is the second most common form of cancer amongst females and also the fifth most cause of cancer deaths worthwide. In case of this particular type of malignancy, early detection is the best form of cure and hence timely and accurate diagnosis of the tumor is extremely vital. Extensive research has been carried out on automating the critical diagnosis procedure as various machine learning algorithms and software tools have been deployed to aid physicians in optimizing the decision task effectively. In this research, we present a novel matrix of an artificial neural network system to effectively classify breast cancer tumors as either malignant or benign. This classification system makes use of both clinical as well as genetic data. Artificial neural networks of different architectures are incorporated in the system to classify both the image based clinical dataset as well as the microarray dataset derived from blood cells. Both the datasets are subjected to indificual analysis to compute the optimum number of input features to the neural network matrix. Randomly selected sample instances from both the clinical and microarray original datasets then serve as an input to the Dempster-Shafer theory of evidence block where the outputs are fused to provide a final diagnostic assessment and compared with the neural network analysis. The results indicate that the fused output of the Dempster-Shafer block significantly outperform the individual classifier's outputs."--Abstract.
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.
Author: Akor Ugwu Publisher: GRIN Verlag ISBN: 334640482X Category : Medical Languages : en Pages : 77
Book Description
Diploma Thesis from the year 2020 in the subject Medicine - Diagnostics, grade: 3.55, , course: Computer Science, language: English, abstract: The study will classify breast cancers into foremost problems: (Benign tumor and Malignant tumor). A benign tumor is a most cancers does now not invade its surrounding tissue or spread around the host. A malignant tumor is another kind of cancers which can invade its surrounding tissue or spread around the frame of the host. Benign cancers on uncommon event can also surely result in someone’s death, but as a fashionable rule they're no longer nearly as horrific because the malignant cancers. The malignant cancers at the contrary are like those killer bees. In this situation, you do not need to be doing something to them or maybe be everywhere near their hive, they will just spread out and attack you emass – they could even kill the individual if they are extreme enough. Manual manner of cancer category into benign and malignant may be very tedious, susceptible to human error and unnecessarily time consuming. The proposed system while constructed can robotically classify the sort of most cancers into the safe (benign) and also the risky (malignant). This machine plays this role through the usage of machine getting to know algorithm. The following is the extensive of this new system: Classification mistakes could be notably removed, early analysis of disorder, removal of possible human mistakes and the device does no longer die. However, the researcher seeks to detect and assess the class of breast using Machine learning.
Author: Khalid Shaikh Publisher: Springer Nature ISBN: 3030592081 Category : Technology & Engineering Languages : en Pages : 107
Book Description
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
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
Author: Ilias Maglogiannis Publisher: Springer Science & Business Media ISBN: 0387342230 Category : Computers Languages : en Pages : 761
Book Description
Artificial Intelligence applications build on a rich and proven theoretical background to provide solutions to a wide range of real life problems. The ever expanding abundance of information and computing power enables researchers and users to tackle higly interesting issues for the first time, such as applications providing personalized access and interactivity to multimodal information based on preferences and semantic concepts or human-machine interface systems utilizing information on the affective state of the user. The purpose of the 3rd IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI) is to bring together researchers, engineers, and practitioners interested in the technical advances and business and industrial applications of intelligent systems. AIAI 2006 is focused on providing insights on how AI can be implemented in real world applications.
Author: Janmenjoy Nayak Publisher: Springer Nature ISBN: 3030719758 Category : Technology & Engineering Languages : en Pages : 461
Book Description
This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.
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.
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.
Author: IEEE Staff Publisher: ISBN: 9781665429825 Category : Languages : en Pages :
Book Description
We solicit high quality original research papers (including significant work in progress) in any aspect of bioinformatics, genomics, and biomedicine New computational techniques and methods and their application in life science and medical domains are especially encouraged
Author: Priyanka Vaidya
Author: Priyanka Vaidya
Author: David Riaño
Author: Akor Ugwu
Author: Khalid Shaikh
Author: Pratheep Kumar
Author: Ilias Maglogiannis
Author: Janmenjoy Nayak
Author: Alberto Tagliafico
Author: Lakhmi C Jain
Author: IEEE Staff