Decision-aiding software is applied in this book to government, personal decisions, law, teaching, decision-analysis research, cross-national decision-making, business and politics.

Appropriate for any course introducing management information systems from a business perspective. This casebook will serve as an ideal complement to most MIS/CIS textbooks. Designed to demonstrate how software can support managerial decision-making activities, this casebook features 24 cases (more than another casebook currently on the market) covering a wide range of functional areas throughout the business, including finance/accounting, HR, production, and information systems. The cases are spread across three difficulty levels basic, intermediate, and advanced. They present common managerial issues and problems, and encourage students to actually use their models to make decisions for the cases characters. They require students to apply spreadsheet, database, Web-page development, and/or presentation graphics software, often in an integrated manner. Many of the cases require students to prepare both written and oral presentations on their solutions. Among the topics covered in MIS Cases: Decision Making with Application Software Second Edition: forecasting, inventory decisions, what-if analyses, pricing strategies, billing decisions, and much more.

An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.

The aim of this book is to clarify what is involved in using decision-aiding software in evaluative decision-making at a non-technical level. Topics covered include the skills that software enhances, the obstacles that it helps overcome, and the applications to diverse fields.

This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

"A very rich book sprinkled with real-life examples as well as battle-tested advice.” —Pierre Haren, VP ILOG, IBM "James does a thorough job of explaining Decision Management Systems as enablers of a formidable business transformation.” —Deepak Advani, Vice President, Business Analytics Products and SPSS, IBM Build Systems That Work Actively to Help You Maximize Growth and Profits Most companies rely on operational systems that are largely passive. But what if you could make your systems active participants in optimizing your business? What if your systems could act intelligently on their own? Learn, not just report? Empower users to take action instead of simply escalating their problems? Evolve without massive IT investments? Decision Management Systems can do all that and more. In this book, the field’s leading expert demonstrates how to use them to drive unprecedented levels of business value. James Taylor shows how to integrate operational and analytic technologies to create systems that are more agile, more analytic, and more adaptive. Through actual case studies, you’ll learn how to combine technologies such as predictive analytics, optimization, and business rules—improving customer service, reducing fraud, managing risk, increasing agility, and driving growth. Both a practical how-to guide and a framework for planning, Decision Management Systems focuses on mainstream business challenges. Coverage includes Understanding how Decision Management Systems can transform your business Planning your systems “with the decision in mind” Identifying, modeling, and prioritizing the decisions you need to optimize Designing and implementing robust decision services Monitoring your ongoing decision-making and learning how to improve it Proven enablers of effective Decision Management Systems: people, process, and technology Identifying and overcoming obstacles that can derail your Decision Management Systems initiative

The use of microcomputers as decision aids in law practice is increasing rapidly. Nagel here shows how developments in software over the last few years are making microcomputers practically indispensable to lawyers as decision aids. This is in contrast to his earlier book on Microcomputers as Decision Aids in Law Practice. It dealt speculatively with ways in which decision-aiding software could be used by lawyers for judicial prediction, litigation strategy, allocating scarce resources, and negotiation-mediation. The book is divided into three parts covering general developments, specific lawyer skills, and application to all fields of law. The first part previews various uses of decision-aiding software by practicing lawyers, including a general discussion of the potential and actual benefits of such software. How decision-aiding software enhances specific lawyer skills comprises the second and largest part of the work. Among the topics discussed are computer-aided counseling, computer-aided mediation, legal policy evaluation and computer-aided advocacy, law prediction, and legal administration. In the third part, Nagel assesses applications of decision-aiding software to all fields of law, with an emphasis on contracts, property, torts, family law, criminal law, constitutional law, economic regulation, international law, civil procedure, and criminal procedure. In a provocative concluding chapter, he deals with the thorny issues of individual ethics and professional responsibility in the context of microcomputers. Because decision-aiding software encourages decision makers to be much more explicit about their goals than they otherwise would be, its use raises questions as to whose goals should be pursued and to what degree. This is a nuts-and-bolts guidebook that will be a valuable tool for practicing attorneys with some knowledge of microcomputers and is recommended reading for legal scholars and law students.