Advancing Healthcare Through Intelligent Clinical Decision Support Systems: Techniques, Applications, and Future Directions

Dear Colleagues,

In healthcare, a variety of complex and continuous decision making processes play key roles in ensuring the delivery of accurate and timely medical care. Healthcare professionals are often faced with a constant flow of decisions across the entire spectrum of healthcare delivery, from initial patient assessment to diagnosis, treatment and subsequent follow-up, in high-pressure and uncertain environments. To address these challenges, the application of artificial intelligence models through different intelligent systems has been integrated with traditional decision support frameworks to provide enhanced, predictive and consistent solutions.

Recognizing the increasing demand for advanced tools to help healthcare professionals navigate this complex landscape of decision making, we propose the creation of a Special Issue dedicated to the exploration and application of intelligent clinical decision support systems (ICDSS) in healthcare. This Special Issue aims to explore the integration of cutting-edge AI technologies and models to facilitate more effective and informed clinical decision making, ultimately improving the quality of patient care.

The development and implementation of intelligent clinical decision support systems (ICDSS) has become essential in supporting healthcare providers' ability to make informed decisions. These systems harness the power of artificial intelligence models to seamlessly handle large volumes of patient data while integrating expertise and knowledge. ICDSS can assist healthcare professionals in several critical aspects of care, including diagnosing diseases, determining appropriate treatment modalities, predicting patient outcomes, and ensuring compliance with best practices. In doing so, they make a significant contribution to improving the overall quality of patient care.

This Special Issue aims to gather contributions that advance the understanding and application of ICDSS in clinical settings. We invite researchers to submit papers on various aspects of ICDSS in the context of healthcare. Potential topics include, but are not limited to:

• Using ICDSS in clinical practice: Presenting case studies and real-world applications of ICDSS to improve patient care, streamline clinical workflows, and enhance medical decision making.
• ICDSS techniques and models: Exploration of the underlying models, algorithms and technologies used in the development of ICDSS, with a focus on their adaptability to the healthcare domain.
• Machine learning and deep learning in ICDSS: Investigating the role of machine learning and deep learning techniques in medical data analysis, image recognition, natural language processing and predictive modelling within clinical decision support systems.
• Expert systems in ICDSS: Discuss the integration of expert knowledge and clinical guidelines into ICDSS to facilitate reasoning and decision making.
• Hybrid systems for ICDSS: Exploring hybrid approaches that combine multiple AI techniques, knowledge and data sources to create more robust and versatile clinical decision support systems.
• Testing and validation of ICDSS: Addressing the challenges and best practices in assessing the accuracy, reliability and safety of ICDSS, including clinical trials and validation studies.
• ICDSS use cases: Highlighting specific scenarios and use cases where ICDSS has demonstrated significant clinical benefit, such as disease diagnosis, treatment recommendation, patient risk assessment and resource allocation.
• Future directions and advances in ICDSS: Explore emerging trends, opportunities and challenges in the development and adoption of ICDSS, including ethical considerations, user acceptance and scalability.

We invite researchers, clinicians and healthcare technology experts to contribute their research, insights and experiences to this Special Issue. Our collective goal is to advance the field of intelligent clinical decision support systems and promote their wider integration into clinical practice, ultimately improving patient outcomes and healthcare delivery.

We look forward to receiving your valuable contributions to this Special Issue as we work together to advance our understanding of ICDSS and their critical role in modern healthcare.

Dr. Manuel Casal-Guisande
Dr. Alberto Comesaña-Campos
Prof. Dr. Jorge Cerqueiro Pequeño
Dr. María Luísa Torres-Durán
Dr. Alberto Fernandez-Villar
Guest Editors

Manuscript Submission Information

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• intelligent clinical decision support systems (ICDSS)
• Healthcare decision-making
• artificial intelligence in healthcare
• machine learning and deep learning in ICDSS
• expert systems in the definition of ICDSS
• expert systems in the definition of ICDSS
• hybrid systems applied in ICDSS
• testing and validation of ICDSS
• future work lines and advances in ICDSS