Abstract
Healthcare providers have to make many decisions as they work through the diagnostic and treatment processes. The Clinical Decision Support Systems are designed to facilitate these decision-making processes by providing computer-based advice to health providers. The importance of having a computer system to help in decision-making, especially in critical care, is well accepted today. The need to have an effective and efficient CDSS integrated into the day-to-day operations and clinical practice has also been emphasized. The key role of CDSS is to facilitate treatment planning by automating clinical knowledge in such a way that it supports integrated care. Such diagnostic systems have the potential to significantly improve patient outcomes by providing accurate and reliable results to the users.
Having CDSS in the healthcare domain allows clinicians to be advised through different perspectives that may have been overlooked due to their busy schedules. The significance of CDSS, especially in diagnosing medical conditions, is increasing rapidly with the increase in the digitization of the complete healthcare system. A significant growth has been observed in the data that is to be processed, which is increasing the reliance on artificial intelligence solutions for better image and non-image diagnostics. While designing such systems, it is also important to take into account the characteristics that would make such systems successful and acceptable to the users and healthcare practitioners. Considerable research has been carried out to design CDSS, but there needs to be continual research to improve upon them.
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