Data Driven Decision Making Advanced Techniques In Healthcare And Business Analytics
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Data-Driven Decision Making: Advanced Techniques in Healthcare and Business Analytics
Author: Krishna prasath Sivaraj Dr Arpit Jain
language: en
Publisher: DeepMisti Publication
Release Date: 2025-02-02
In today’s data-driven world, decisions are no longer based on intuition alone. Organizations in healthcare and business are increasingly leveraging advanced analytics to extract meaningful insights, optimize operations, and create value. The ability to make data-driven decisions has become a defining factor in achieving success, fostering innovation, and navigating complex challenges. Data-Driven Decision Making: Advanced Techniques in Healthcare and Business Analytics is a comprehensive guide to mastering the tools, methods, and strategies that empower professionals to transform raw data into actionable knowledge. This book explores the critical intersection of analytics and decision-making, offering readers the expertise needed to thrive in data-intensive environments. Key themes covered include: • The foundations of data-driven decision-making and its role in strategic planning. • Advanced analytics techniques, such as predictive modeling, machine learning, and real- time data processing. • Practical applications in healthcare, including patient outcome prediction, resource allocation, and personalized medicine. • Use cases in business, such as customer segmentation, financial forecasting, and operational optimization. • Ethical considerations, data governance, and strategies for ensuring compliance with evolving regulations. This book is designed for healthcare professionals, business leaders, data scientists, and analysts who seek to harness the power of data for impactful decision-making. Whether you are solving problems in healthcare delivery or driving business growth, the methodologies presented here will equip you to make informed, evidence-based decisions. The journey to mastering data-driven decision-making is both a technical and strategic endeavor. Through this book, we aim to inspire you to unlock the full potential of analytics, delivering better outcomes for your organization and the people it serves. Let this guide be your companion as you explore the transformative power of advanced analytics in healthcare and business. Authors
Smart Healthcare System Design
Author: S. K. Hafizul Islam
language: en
Publisher: John Wiley & Sons
Release Date: 2021-06-29
SMART HEALTHCARE SYSTEM DESIGN This book deeply discusses the major challenges and issues for security and privacy aspects of smart health-care systems. The Internet-of-Things (IoT) has emerged as a powerful and promising technology, and though it has significant technological, social, and economic impacts, it also poses new security and privacy challenges. Compared with the traditional internet, the IoT has various embedded devices, mobile devices, a server, and the cloud, with different capabilities to support multiple services. The pervasiveness of these devices represents a huge attack surface and, since the IoT connects cyberspace to physical space, known as a cyber-physical system, IoT attacks not only have an impact on information systems, but also affect physical infrastructure, the environment, and even human security. The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies. Smart Healthcare System Design covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus is on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations. Audience: Researchers and industry engineers in information technology, artificial intelligence, cyber security, as well as designers of healthcare systems, will find this book very valuable.
Business Analytics: Data-Driven Decision Making
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