Download or read book Machine Learning for Liver Disease Classification written by Benjamin D. Jesty and published by . This book was released on 2019 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book DATA SCIENCE WORKSHOP Liver Disease Classification and Prediction Using Machine Learning and Deep Learning with Python GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2023-08-09 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this project, Data Science Workshop focused on Liver Disease Classification and Prediction, we embarked on a comprehensive journey through various stages of data analysis, model development, and performance evaluation. The workshop aimed to utilize Python and its associated libraries to create a Graphical User Interface (GUI) that facilitates the classification and prediction of liver disease cases. Our exploration began with a thorough examination of the dataset. This entailed importing necessary libraries such as NumPy, Pandas, and Matplotlib for data manipulation, visualization, and preprocessing. The dataset, representing liver-related attributes, was read and its dimensions were checked to ensure data integrity. To gain a preliminary understanding, the dataset's initial rows and column information were displayed. We identified key features such as 'Age', 'Gender', and various biochemical attributes relevant to liver health. The dataset's structure, including data types and non-null counts, was inspected to identify any potential data quality issues. We detected that the 'Albumin_and_Globulin_Ratio' feature had a few missing values, which were subsequently filled with the median value. Our exploration extended to visualizing categorical distributions. Pie charts provided insights into the proportions of healthy and unhealthy liver cases among different gender categories. Stacked bar plots further delved into the connections between 'Total_Bilirubin' categories and the prevalence of liver disease, fostering a deeper understanding of these relationships. Transitioning to predictive modeling, we embarked on constructing machine learning models. Our arsenal included a range of algorithms such as Logistic Regression, Support Vector Machines, K-Nearest Neighbors, Decision Trees, Random Forests, Gradient Boosting, Extreme Gradient Boosting, Light Gradient Boosting. The data was split into training and testing sets, and each model underwent rigorous evaluation using metrics like accuracy, precision, recall, F1-score, and ROC-AUC. Hyperparameter tuning played a pivotal role in model enhancement. We leveraged grid search and cross-validation techniques to identify the best combination of hyperparameters, optimizing model performance. Our focus shifted towards assessing the significance of each feature, using techniques such as feature importance from tree-based models. The workshop didn't halt at machine learning; it delved into deep learning as well. We implemented an Artificial Neural Network (ANN) using the Keras library. This powerful model demonstrated its ability to capture complex relationships within the data. With distinct layers, activation functions, and dropout layers to prevent overfitting, the ANN achieved impressive results in liver disease prediction. Our journey culminated with a comprehensive analysis of model performance. The metrics chosen for evaluation included accuracy, precision, recall, F1-score, and confusion matrix visualizations. These metrics provided a comprehensive view of the model's capability to correctly classify both healthy and unhealthy liver cases. In summary, the Data Science Workshop on Liver Disease Classification and Prediction was a holistic exploration into data preprocessing, feature categorization, machine learning, and deep learning techniques. The culmination of these efforts resulted in the creation of a Python GUI that empowers users to input patient attributes and receive predictions regarding liver health. Through this workshop, participants gained a well-rounded understanding of data science techniques and their application in the field of healthcare.

Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Advances in Decision Sciences Image Processing Security and Computer Vision written by Suresh Chandra Satapathy and published by Springer. This book was released on 2019-07-25 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the First International Conference on Emerging Trends in Engineering (ICETE), held at University College of Engineering and organised by the Alumni Association, University College of Engineering, Osmania University, in Hyderabad, India on 22–23 March 2019. The proceedings of the ICETE are published in three volumes, covering seven areas: Biomedical, Civil, Computer Science, Electrical & Electronics, Electronics & Communication, Mechanical, and Mining Engineering. The 215 peer-reviewed papers from around the globe present the latest state-of-the-art research, and are useful to postgraduate students, researchers, academics and industry engineers working in the respective fields. Volume 2 presents papers on the theme “Advances in Decision Sciences, Image Processing, Security and Computer Vision – International Conference on Emerging Trends in Engineering (ICETE)”. It includes state-of-the-art technical contributions in the areas of electronics and communication engineering and electrical and electronics engineering, discussing the latest sustainable developments in fields such as signal processing and communications; GNSS and VLSI; microwaves and antennas; signal, speech and image processing; power systems; and power electronics.

Download or read book Deep Learning Applications and Intelligent Decision Making in Engineering written by Senthilnathan, Karthikrajan and published by IGI Global. This book was released on 2020-10-23 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process. Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.

Download or read book Artificial Intelligence Machine Learning and Deep Learning in Precision Medicine in Liver Diseases written by Tung-Hung Su and published by Elsevier. This book was released on 2023-08-20 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine and Liver Diseases: Concept, Technology, Application, and Perspectives combines four major applications of artificial intelligence (AI) within the field of clinical medicine specific to liver diseases: radiology imaging, electronic health records, pathology, and multiomics. The book provides a state-of-the-art summary of AI in precision medicine in hepatology, clarifying the concept and technology of AI and pointing to the current and future applications of AI within the field of hepatology. Coverage includes data preparation, methodology and application within disease-specific cases in fibrosis, viral and steatohepatitis, cirrhosis, hepatocellular carcinoma, acute liver failure, liver transplantation, and more. The ethical and legal issues of AI and future challenges and perspectives are also discussed. By highlighting many new AI applications which can further research, diagnosis, and treatment, this reference is the perfect resource for both practicing hepatologists and researchers focused on AI applications in medicine. Introduces the concept of AI and machine learning of precision medicine in the field of hepatology Discusses current challenges of AI in healthcare and proposes future tasks for AI in new workflows of healthcare Provides real-world applications from domain experts in clinical medicine

Download or read book Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning written by Rani, Geeta and published by IGI Global. This book was released on 2020-10-16 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Download or read book 2020 6th International Conference on Advanced Computing and Communication Systems ICACCS written by IEEE Staff and published by . This book was released on 2020-03-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 2020 International Conference on Advanced Computing & Communication Systems (ICACCS) aims at exploring the interface between the industry and real time environment with state of the art techniques ICACCS 2020 publishes original and timely research papers and survey articles in current areas of sustainable computing, energy, smart city, temperature, power and environment related research areas of current importance to readers

Download or read book Machine Learning Application written by 鄭羽涵 and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Classification of US Liver Images Using Machine Learning Techniques written by Suganya Ramamoorthy and published by LAP Lambert Academic Publishing. This book was released on 2014-11-04 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of medical imaging has experienced a period of rapid development over the last 2 decade has consequently revolutionized the way in which modern medicine is practiced.The disease and their symptoms are highly varying and always a need for a continuous update of knowledge for the doctors and medical analyst.The diseases fall into different categories and a small variation of symptoms may leave to some other categories of diseases.The work concentrates on diagnosing diseases like cyst, fatty, Hepatoma, Hemangioma and Cirrhosis from ultrasound liver images.The contribution of this book relies on following areas: Pre-processing by speckle reduction, Image registration, feature extraction, classification & retrieval.This is further supplemented by the medical analyst for a continuous treatment process.This book provides an automated system that could retrieve ultrasound liver images based on user's interest to a level of providing decision support is of high need.This book helps for the medical analyst to take decision before treatment and planning surgery. It provides sound knowledge to researcher who are all working in problems involved in ultrasound medical imagin

Download or read book Computational Vision and Bio Inspired Computing written by S. Smys and published by Springer Nature. This book was released on 2021-06-14 with total page 871 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers from the 4th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2020), held in Coimbatore, India, from November 19 to 20, 2020. This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

Download or read book Data Engineering and Intelligent Computing written by Vikrant Bhateja and published by Springer Nature. This book was released on 2021-05-04 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features a collection of high-quality, peer-reviewed papers presented at the Fourth International Conference on Intelligent Computing and Communication (ICICC 2020) organized by the Department of Computer Science and Engineering and the Department of Computer Science and Technology, Dayananda Sagar University, Bengaluru, India, on 18–20 September 2020. The book is organized in two volumes and discusses advanced and multi-disciplinary research regarding the design of smart computing and informatics. It focuses on innovation paradigms in system knowledge, intelligence and sustainability that can be applied to provide practical solutions to a number of problems in society, the environment and industry. Further, the book also addresses the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and health care.

Download or read book Intelligent Computing in Control and Communication written by G.T. Chandra Sekhar and published by Springer Nature. This book was released on 2021-01-04 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of peer-reviewed papers presented at the First International Conference on Intelligent Computing in Control and Communication (ICCC 2020). It comprises interesting topics in the field of applications of control engineering, communication and computing technology. As the current world is witnessing the use of various intelligent techniques for their independent problem solving, so this book may have a wide importance for all range of researchers and scholars. The book serves as a reference for researchers, professionals and students from across electrical, electronic and computer engineering disciplines.

Download or read book Conference Proceedings of ICDLAIR2019 written by Meenakshi Tripathi and published by Springer Nature. This book was released on 2021-02-08 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings book includes the results from the International Conference on Deep Learning, Artificial Intelligence and Robotics, held in Malaviya National Institute of Technology, Jawahar Lal Nehru Marg, Malaviya Nagar, Jaipur, Rajasthan, 302017. The scope of this conference includes all subareas of AI, with broad coverage of traditional topics like robotics, statistical learning and deep learning techniques. However, the organizing committee expressly encouraged work on the applications of DL and AI in the important fields of computer/electronics/electrical/mechanical/chemical/textile engineering, health care and agriculture, business and social media and other relevant domains. The conference welcomed papers on the following (but not limited to) research topics: · Deep Learning: Applications of deep learning in various engineering streams, neural information processing systems, training schemes, GPU computation and paradigms, human–computer interaction, genetic algorithm, reinforcement learning, natural language processing, social computing, user customization, embedded computation, automotive design and bioinformatics · Artificial Intelligence: Automatic control, natural language processing, data mining and machine learning tools, fuzzy logic, heuristic optimization techniques (membrane-based separation, wastewater treatment, process control, etc.) and soft computing · Robotics: Automation and advanced control-based applications in engineering, neural networks on low powered devices, human–robot interaction and communication, cognitive, developmental and evolutionary robotics, fault diagnosis, virtual reality, space and underwater robotics, simulation and modelling, bio-inspired robotics, cable robots, cognitive robotics, collaborative robotics, collective and social robots and humanoid robots It was a collaborative platform for academic experts, researchers and corporate professionals for interacting their research in various domain of engineering like robotics, data acquisition, human–computer interaction, genetic algorithm, sentiment analysis as well as usage of AI and advanced computation in various industrial challenges based applications such as user customization, augmented reality, voice assistants, reactor design, product formulation/synthesis, embedded system design, membrane-based separation for protecting environment along with wastewater treatment, rheological properties estimation for Newtonian and non-Newtonian fluids used in micro-processing industries and fault detection.

Download or read book Accuracy of rule extraction using a recursive rule extraction algorithm with continuous attributes combined with a sampling selection technique for the diagnosis of liver disease written by Yoichi Hayashi and published by Infinite Study. This book was released on with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although liver cancer is the second most common cause of death from cancer worldwide, because of the limited accuracy and interpretability of extracted classification rules, the diagnosis of liver disease remains difficult. In addition, hepatitis, which is inflammation of the liver, can progress to fibrosis, cirrhosis, or even liver cancer.

Download or read book Proceedings of International Conference on Recent Trends in Machine Learning IoT Smart Cities and Applications written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on 2020-10-17 with total page 998 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected research papers presented at the International Conference on Recent Trends in Machine Learning, IOT, Smart Cities & Applications (ICMISC 2020), held on 29–30 March 2020 at CMR Institute of Technology, Hyderabad, Telangana, India. Discussing current trends in machine learning, Internet of things, and smart cities applications, with a focus on multi-disciplinary research in the area of artificial intelligence and cyber-physical systems, this book is a valuable resource for scientists, research scholars and PG students wanting formulate their research ideas and find the future directions in these areas. Further, it serves as a reference work anyone wishing to understand the latest technologies used by practicing engineers around the globe.

Download or read book Computational Analysis and Deep Learning for Medical Care written by Amit Kumar Tyagi and published by John Wiley & Sons. This book was released on 2021-08-24 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.