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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Morgan Kaufmann | Boston, MA : Safari
    ISBN: 9780128034989
    Language: English
    Pages: 1 online resource (366 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Applied Computing in Medicine and Health is a comprehensive presentation of on-going investigations into current applied computing challenges and advances, with a focus on a particular class of applications, primarily artificial intelligence methods and techniques in medicine and health. Applied computing is the use of practical computer science knowledge to enable use of the latest technology and techniques in a variety of different fields ranging from business to scientific research. One of the most important and relevant areas in applied computing is the use of artificial intelligence (AI) in health and medicine. Artificial intelligence in health and medicine (AIHM) is assuming the challenge of creating and distributing tools that can support medical doctors and specialists in new endeavors. The material included covers a wide variety of interdisciplinary perspectives concerning the theory and practice of applied computing in medicine, human biology, and health care. Particular attention is given to AI-based clinical decision-making, medical knowledge engineering, knowledge-based systems in medical education and research, intelligent medical information systems, intelligent databases, intelligent devices and instruments, medical AI tools, reasoning and metareasoning in medicine, and methodological, philosophical, ethical, and intelligent medical data analysis. Discusses applications of artificial intelligence in medical data analysis and classifications Provides an overview of mobile health and telemedicine with specific examples and case studies Explains how behavioral intervention technologies use smart phones to support a patient centered approach Covers the design and implementation of medical decision support systems in clinical practice using an applied case study approach
    Note: Online resource; Title from title page (viewed August 21, 2015)
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  • 2
    ISBN: 9789819907410
    Language: English
    Pages: 1 Online-Ressource(XXII, 548 p. 233 illus., 171 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Lecture Notes on Data Engineering and Communications Technologies 165
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence. ; Big data. ; Internet of things. ; Computer vision.
    Abstract: Part I: Artificial Intelligence -- Extractive Text Summarization Using Syntactic Sub- Graph Models -- Analysis of Big Five Personality Factors to determine the Appropriate Type of Career using the C4.5 Algorithm -- Predicting Disaster Type from Social Media Imagery via Deep Neural Networks Directed by Visual Attention -- Dissemination Management for Official Statistics Using Artificial Intelligence-Based Media Monitoring -- Part II: Computational Vision -- A Naive but Effective Post-Processing Approach for Dark Channel Prior (DCP) -- COVID-19 Face Mask Classification Using Deep Learning -- Gender Classification Using Transfer Learning and Fine-Tuning -- Multi-Language Recognition Translator by Using the Convolutional Neural Network (CNN) Algorithm and Optical Character Recognition (OCR) -- Autonomous Driving Through Road Segmentation Based on Computer Vision Techniques -- Part III: Cybersecurity -- Phishing Attack Types and Mitigation: A Survey -- A Review of Privacy Protection Methods for Smart Homes Against Wireless Snooping Attack -- Development of Graph-Based Knowledge on Ransom-Ware Attacks Using Twitter Data -- Part IV: Big Data Analytics -- BigMDHealth: Supporting Multidimensional Big Data Management and Analytics over Big Healthcare Data via Effective and Efficient Multidimensional Aggregate Queries over Key-Value Stores (Prof Alredo's paper) -- Design and Implementation of Data Warehouse Solution at Kumpulan Wang Persaraan (KWAP) -- Consumer Behavior Prediction During Covid-19 Pandemic Conditions Using Sentiment Analytics -- Big Data Application on Prediction of HDD Manufacturing Process Performance -- Visualising Economic Situation Through Malaysia Economic Recovery Dashboard (MERD) -- Part V: Machine/Deep Learning -- Lung Nodules Classification Using Convolutional Neural Network with Transfer Learning -- Plant Growth Phase Classification Using Deep Neural Network -- The Implementation of Genetic Algorithm-Ensemble Learning on QSAR Study of Diacylglycerol Acyltransferase-1(DGAT1) Inhibitors as Anti-Diabetes -- Classification of Exercise Game Data for Rehabilitation Using Machine Learning Algorithms -- SDDLA: A New Architecture for Secured Decentralized Distributed Learning -- Gated Memory Unit: A Novel Recurrent Neural Network Architecture for Sequential Analysis -- Multi-Class Classification for Breast Cancer with High Dimensional Microarray Data Using Machine Learning Classifier -- Predicting Risks of Late Delivery to Online Shopping Customers Using Machine Learning Techniques -- Quora Insincere Questions Classification Using Attention Based Model -- Suicide Ideation Detection: A Comparative Study of Sequential and Transformer Hybrid Algorithms -- Well Log Data Preparation and Effective Utilization of Drilling Parameters Using Data Science Based Approaches -- Deep Learning-Based Approach for Classifying the Severity of Metal Corrosion Using SEM Images -- Insurance Risk Prediction Using Machine Learning -- Loan Default Forecasting Using StackNet -- Part VI: Statistical Learning -- Neural Network Autoregressive Model for Forecasting Malaysia Under-5 Mortality -- Robustness of Support Vector Regression and Random Forest Models: A Simulation Study -- The Impact of Restrictions Community Activities on COVID-19 Transmission: A Case Study in Sumatra Island, Indonesia -- Predicting Internet Usage for Digital Finance Services: Multitarget Classification Using Vector Generalized Additive Model with SMOTE-NC -- Part VII: Text Mining and Classification -- Identifying Topic Modeling Technique in Evaluating Textual Datasets -- Y-X-Y Encoding for Identifying Types of Sentence Similarity -- Evaluation of Extractive and Abstract Methods in Text Summarization.
    Abstract: The book presents selected papers from International Conference on Data Science and Emerging Technologies (DaSET 2022), held online at UNITAR International University, Malaysia, during December 20–21, 2022. This book aims to present current research and applications of data science and emerging technologies. The deployment of data science and emerging technology contributes to the achievement of the Sustainable Development Goals for social inclusion, environmental sustainability, and economic prosperity. Data science and emerging technologies such as artificial intelligence and blockchain are useful for various domains such as marketing, health care, finance, banking, environmental, and agriculture. An important grand challenge in data science is to determine how developments in computational and social-behavioral sciences can be combined to improve well-being, emergency response, sustainability, and civic engagement in a well-informed, data-driven society. The topics of this book include, but not limited to: artificial intelligence, big data technology, machine and deep learning, data mining, optimization algorithms, blockchain, Internet of Things (IoT), cloud computing, computer vision, cybersecurity, augmented and virtual reality, cryptography, and statistical learning.
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