Artificial Intelligence

Review of Marketing Researchpushes the boundaries of marketing--broadening the marketing concept to make the world a better place. Here, leading scholars explore how marketing is currently shaping, and being shaped by, the evolution of Artificial Intelligence (AI). Topics covered include the effects of AI on: economics; personalisation; pricing; content generation; the identification, structuring, and prioritization of customer needs; customer feedback; Natural Language Processing; image analytics; deep learning; and the anthropomorphism of AI, such as in virtual assistants and chatbots. Each chapter provides thought provoking discussions which will be relevant to researchers, professionals, and students.

Broad coverage of approaches for AI, big data analytics and machine learning-based neurological research; machine learning techniques to detect neurological diseases at the cellular level, image segmentation, classification, image AI techniques for the early detection of neurological disease and deep learning applications using brain imaging methods like EEG, MEG, fMRI, fNIRS and PET for seizure prediction or neuromuscular rehabilitation.

Presents updates on the application of machine learning and deep learning techniques in medical procedures. Topics covered in the book include 1) Artificial Intelligence (AI) applications in cancer diagnosis and therapy,2) Updates in AI applications in the medical industry, 3) the use of AI in studying the COVID-19 pandemic in China, 4) AI applications in clinical oncology (including AI-based mining for pulmonary nodules and the use of AI in understanding specific carcinomas), 5) AI in medical imaging. Each chapter presents information on related subtopics in a reader friendly format.

Historic development and current status, existing and projected AI applications, and present and potential future impact on the United States and the world; explain theories and innovations like Moore's Law, mindcloning, and Technological Singularity that drive AI research and debate.

The authors explain that the two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, often without realizing it. The rise of AI is shifting prediction from humans to machines, relieving people from this cognitive load while increasing the speed and accuracy of decisions. This sets the stage for a flourishing of new decisions and has profound implications for system-level innovation. Redesigning systems of interdependent decisions takes time--many industries are in the quiet before the storm--but when these new systems emerge, they can be disruptive on a global scale. Decision-making confers power. In industry, power confers profits; in society, power confers control. This process will have winners and losers, and the authors show how businesses can leverage opportunities, as well as protect their positions.

The book begins with explaining why healthcare workers, whether they work on the frontlines or in management, need to be strong critical thinkers. It breaks down "critical thinking" into its key elements and provides methods that readers can use to help them to master critical thinking and grow to become elite critical thinkers. Includes tips on how to handle ad hoc conversations with supervisors, coworkers, patients, residents, and other stakeholders. Examining how AI- and IT-related developments will transform the healthcare ecosystem in the coming years, the book identifies key mindsets and strategies for thriving in technologically rich healthcare environments.