Artificial Intelligence and Machine Learning in Healthcare

This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.

Produk Detail:

  • Author : Ankur Saxena
  • Publisher : Springer Nature
  • Pages : 228 pages
  • ISBN : 9811608113
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKArtificial Intelligence and Machine Learning in Healthcare

Artificial Intelligence and Machine Learning in Healthcare

Artificial Intelligence and Machine Learning in Healthcare
  • Author : Ankur Saxena,Shivani Chandra
  • Publisher : Springer Nature
  • Release : 30 November 2021
GET THIS BOOKArtificial Intelligence and Machine Learning in Healthcare

This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed

Machine Learning and AI for Healthcare

Machine Learning and AI for Healthcare
  • Author : Arjun Panesar
  • Publisher : Apress
  • Release : 04 February 2019
GET THIS BOOKMachine Learning and AI for Healthcare

Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare
  • Author : Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar
  • Publisher : Academic Press
  • Release : 26 April 2021
GET THIS BOOKMachine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and

Artificial Intelligence and Machine Learning in Public Healthcare

Artificial Intelligence and Machine Learning in Public Healthcare
  • Author : KC Santosh,Loveleen Gaur
  • Publisher : Springer
  • Release : 22 January 2022
GET THIS BOOKArtificial Intelligence and Machine Learning in Public Healthcare

This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention

Big Data and Artificial Intelligence for Healthcare Applications

Big Data and Artificial Intelligence for Healthcare Applications
  • Author : Ankur Saxena,Nicolas Brault,Shazia Rashid
  • Publisher : CRC Press
  • Release : 15 June 2021
GET THIS BOOKBig Data and Artificial Intelligence for Healthcare Applications

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early

Deep Learning in Healthcare

Deep Learning in Healthcare
  • Author : Yen-Wei Chen,Lakhmi C. Jain
  • Publisher : Springer Nature
  • Release : 18 November 2019
GET THIS BOOKDeep Learning in Healthcare

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output,

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
  • Author : Parag Mahajan
  • Publisher : Medmantra, LLC
  • Release : 01 February 2021
GET THIS BOOKArtificial Intelligence in Healthcare

① Do you know what AI is doing to improve our health and wellbeing? ② Does this new technology concern you, or impress you? ③ Do you want to know more about the future of AI in healthcare? Technology continues to advance at a pace that can seem bewildering. Nowhere else is it moving faster than in the health sector, where ♥AI is now being used to improve millions of lives♥. In this book, ◆ Artificial Intelligence in Healthcare: AI, Machine Learning, and Deep

Data Analytics in Bioinformatics

Data Analytics in Bioinformatics
  • Author : Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang
  • Publisher : John Wiley & Sons
  • Release : 20 January 2021
GET THIS BOOKData Analytics in Bioinformatics

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

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
  • Author : David Riaño,Szymon Wilk,Annette ten Teije
  • Publisher : Springer
  • Release : 19 June 2019
GET THIS BOOKArtificial Intelligence in Medicine

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.

Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
  • Author : Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
  • Publisher : Academic Press
  • Release : 20 November 2020
GET THIS BOOKMachine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness

Alginates

Alginates
  • Author : Anonim
  • Publisher : BoD – Books on Demand
  • Release : 05 February 2020
GET THIS BOOKAlginates

Alginates are polysaccharides found in both the intercellular matrix of brown algae and extracellularly covering some species of bacteria. Alginate varies in composition of the algae from 20% to 60% dry matter, but on average brown algae species has 40% alginate. Alginate from brown algae occurs as gels containing sodium, calcium, strontium, magnesium, and barium ions. They are widely used by the food industry, giving foods texture properties such as thickening, adhesion, emulsification, gelling, or fullness. This book covers the latest uses of

Artificial Intelligence

Artificial Intelligence
  • Author : Sandeep Reddy
  • Publisher : CRC Press
  • Release : 03 December 2020
GET THIS BOOKArtificial Intelligence

The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems
  • Author : Om Prakash Jena,Bharat Bhushan,Nitin Rakesh,Parma Nand Astya,Yousef Farhaoui
  • Publisher : CRC Press
  • Release : 01 December 2021
GET THIS BOOKMachine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

The paramountcy of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and led to the modern age of machine learning, deep learning and internet of medical things (IoMT) with their proliferation, mobility and agility. This book will expose different dimensions of applications for computational intelligence and will explain its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning

Blockchain and Machine Learning for e-Healthcare Systems

Blockchain and Machine Learning for e-Healthcare Systems
  • Author : Balusamy Balamurugan,Naveen Chilamkurti,T. Lucia Agnes Beena,T. Poongodi
  • Publisher : Institution of Engineering and Technology
  • Release : 13 November 2020
GET THIS BOOKBlockchain and Machine Learning for e-Healthcare Systems

Blockchain and machine learning technologies can mitigate healthcare issues such as slow access to medical data, poor system interoperability, lack of patient agency, and data quality and quantity for medical research. Blockchain technology facilitates and secures the storage of information in such a way that doctors can see a patient's entire medical history, but researchers see only statistical data instead of any personal information. Machine learning can make use of this data to notice patterns and give accurate predictions, providing

Smart Manufacturing

Smart Manufacturing
  • Author : Tan Yen Kheng
  • Publisher : BoD – Books on Demand
  • Release : 14 January 2021
GET THIS BOOKSmart Manufacturing

Smart manufacturing uses big data, the Internet of things (IoT) and the Internet of Services (IoS), and flexible and dynamic workforces to cope with ever-increasing demand in low-volume, high-mix production. Companies worldwide are already pivoting towards dynamic and reconfigurable production as a smarter way to build and make things. As such, this book discusses the next generation of manufacturing, which will involve the transformational convergence of intelligent machines, powerful computing and analytics, and unprecedented networking of people, products, and services.