Intelligent decision support systems (IDSS) use artificial intelligence (AI) to help human beings make better decisions by providing them with relevant information and recommendations. The IDSS uses a variety of data sources, collects and processes them to generate useful information for analysts. Artificial intelligence is the backbone of effective decision support systems. A decision support system helps facilitate decision-making by a team or company based on data.
AI capabilities go one step further and automate decision-making for companies, which is also known as an expert system. An intelligent decision support system (IDSS) is a decision support system that makes extensive use of artificial intelligence (AI) techniques. The use of AI techniques in management information systems has a long history; in fact, terms such as knowledge-based systems (KBS) and intelligent systems have been used since the early 1980s to describe the components of management systems, but it is believed that the term intelligent decision support system originated with Clyde Holsapple and Andrew Whinston in the late 1970s. Examples of specialized intelligent decision support systems include flexible manufacturing systems (FMS), intelligent marketing decision support systems, and medical diagnostic systems.
We have developed an AI-based decision support system, together with a large energy company, that analyzes large data flows to help decision making based on exceeding certain thresholds. The purpose of AI techniques integrated into an intelligent decision support system is to allow a computer to carry out these tasks, while emulating human capabilities as faithfully as possible. More generally, DSS can help healthcare companies analyze patient data to improve overall business performance and patient outcomes and reduce healthcare costs. AI works by creating artificial neural networks, a series of algorithms that identify relationships and patterns in data that can mimic the way the human brain works.
For example, intelligent agents that perform complex cognitive tasks without the need for human intervention have been used in a variety of decision-making support applications. Artificial intelligence techniques for decision-making, or augmented analysis, are an effective way for companies to use data to make intelligent business decisions with confidence. Radiologists use clinical decision support systems in the form of AI-based image processing software to help detect cancer. However, in reality, they are simply algorithms and, although they are not so visually interesting, they are already very useful for improving decision-making in business workflows and other processes.
The methodology of the decision support system can be fully managed by artificial intelligence (AI), human beings, decision makers, or a combination of both.
