Samuel Fosso Wamba – författare

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists.

Features:

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists.

Features:

This book provides the key technologies involved in an organization’s digital transformation. It offers a deep understanding of the key technologies (Blockchain, AI, Big Data, IoT, etc.) involved and details the impact, the decision-making process, and the interplay between technologies, business models, and operations.

Managing the Digital Transformation: Aligning Technologies, Business Models, and Operations provides frameworks and models to support digital transformation projects. The book presents the importance of digital transformation as a resilience approach to the operations processes and business models. It covers the essential elements integrating the technology, the organizations, the operations, and supply chain management used to move toward digital transformation. Concepts and mini-case studies are included to provide a deeper understanding of digital transformation projects with a holistic view. The book also examines the role that digital transformation plays with consideration of inter-organizational and intra-organizational capabilities, along with the role of digital culture, the worker’s skills, business models, reconfiguration, as well as an operations optimization angle.

Practitioners, consultants, governments, managers, scholars, and anyone interested in digital transformation will find the contents of this book very useful.

This book provides the key technologies involved in an organization’s digital transformation. It offers a deep understanding of the key technologies (Blockchain, AI, Big Data, IoT, etc.) involved and details the impact, the decision-making process, and the interplay between technologies, business models, and operations.

Managing the Digital Transformation: Aligning Technologies, Business Models, and Operations provides frameworks and models to support digital transformation projects. The book presents the importance of digital transformation as a resilience approach to the operations processes and business models. It covers the essential elements integrating the technology, the organizations, the operations, and supply chain management used to move toward digital transformation. Concepts and mini-case studies are included to provide a deeper understanding of digital transformation projects with a holistic view. The book also examines the role that digital transformation plays with consideration of inter-organizational and intra-organizational capabilities, along with the role of digital culture, the worker’s skills, business models, reconfiguration, as well as an operations optimization angle.

Practitioners, consultants, governments, managers, scholars, and anyone interested in digital transformation will find the contents of this book very useful.

With contributions from leading academics and practitioners, the Handbook analyses how big data analytics can be used in different sectors, including detecting credit fraud in the financial sector, identifying potential diseases in health care, and increasing customer loyalty in the telecommunication sector. Chapters explore the use of artificial intelligence in accounting, the construction of successful data science ecosystems using the public cloud, and transformational models of personal data protection in the digital era. The Handbook also discusses the difficulties of adopting a data science platform and how the public cloud can aid companies in overcoming these challenges.

Exploring how industries rely on predictive analytics to improve their decision-making, this Handbook will be essential reading for students and scholars in business analytics, economics, information systems, innovation and technology, and research methods. It will also benefit data analysts, economists, human resource managers, marketers, neuroscientists, and social science researchers.