Enhancing Decision-making in Healthcare with Conversational AI and Information Systems

Scope

Although conversational AI typically encompasses technologies that enable spontaneous communications involving machines and humans through the use of AI-enabled voice and text recognition, it could refer to a wide range of systems. Multimodal AI, thus, encompasses both voice-activated and text-based technologies. Text-based technologies rely on visual screens for communication input and manufacturing, whereas voice-enabled systems need microphones and speakers. an interactive online decision-making tool to help healthcare beneficiaries choose their plans on their own, given the variety of available alternatives and their limited skills with computers. Based on their growing capacities, conversational agents could become more and more integral parts of health and medical services, helping doctors during consultations, helping clients who are struggling with behaviour modification, or helping clients and the elderly in their homes. There may be safety risks associated with these options, which might endanger patients. As far as we are aware, an extensive analysis of this technological application in healthcare has been done.

The use of AI in healthcare is transforming health care and medical science. AI scientists and healthcare professionals must work together in order for AI technology to reach its full capabilities. Improvements in therapy and diagnostics are a key area of cooperation. By combining AI techniques with patient data, healthcare professionals may benefit from improved medical precision, early sickness recognition, and precise treatment scheduling. The implications are better patient outcomes and better healthcare services. Collaboration also enables the development of personalised healthcare approaches. Treatments and therapeutic effectiveness are enhanced as a consequence of this group effort. AI and healthcare professionals collaborating facilitates the development of systems that support clinical decision-making. Although the expanding use of medical IT has numerous benefits, there are now additional challenges with regard to patient data security. Conversational artificial intelligence devices with decision-making capabilities are becoming more and more helpful in the healthcare sector as ways to enhance administrative and patient interaction operations. Robust safety regulations must be in place to safeguard healthcare data because of its sensitive aspect.

The healthcare industry is now dealing with an assortment of difficulties, including an information deficit and sophistication that is only growing. This leads to ineffective decision-making, which might lead to mistakes. Modern technology makes the healthcare industry run more smoothly and with a stronger focus on the needs of the patient. These systems are currently only being used at very low rates, and there are few examples of successful implementations where the AI really benefits patients or physicians. AI, or designated technological decision support systems, holds the key to making the healthcare industry more precise, efficient, and patient-focused as a result of its digital transformation. In this special issue, we investigate the need for these systems and the best ways to properly integrate them into clinical practice. We offer a methodical strategy based on our theoretical structure to address this.

The topics relevant to this special issue include but are not limited to:

Conversational AI neutralising techniques: enhancing cybersecurity and privacy assessment
Impact of Decision Phases and Conversational AI Support on e-Healthcare Decision Toolkit
Healthcare transformation: using AI's capabilities in the contemporary generation
Utilising artificial intelligence in collaborative health: uses, consequences, and prospects
Understanding aspects impacting on technology aids in making decisions regarding healthcare
Conversational mediators in the categorization of healthcare and a theoretical framework
Structured AI Assistance for Healthcare Sector Decision-Making: Challenges and Advantages
Important aspects of conversational agents' information integrity in the healthcare industry
Individual autonomy of self-determination as a basis for AI-assisted decision making
Artificial intelligence's position in medical therapy is revolutionising healthcare
Methodology for evaluating AI-powered interactive programmes in health care