Artificial intelligence (AI) has been proliferating in recent years regarding software algorithms, equipment execution, and applications in a vast number of areas. New advancements and forward leaps will keep on pushing the frontier, widening the scope of AI application and quick improvements are imagined sooner rather than later. Because of the quick advancement of AI programming and equipment advances, AI has been applied in different specialized fields, such as the Internet of Things (IoT), machine vision, automated driving systems, robotics, and natural language processing.

Analysts in the biomedical field have been effectively attempting to apply AI to help improve examination and treatment results and, subsequently, increment the viability of the overall healthcare industry. The advantages that AI can offer to biomedicine were imagined several decades sooner. The AI assistant assesses the person’s symptoms and finds the most appropriate treatment option to the doctor from its analysis. Meanwhile, cognitive computing comes up with information that helps the doctor in providing treatment - where the doctor himself can take the final decision. Thus, for smarter decision making and better human assisting, cognitive computing plays an important role. Evidently, both AI and cognitive computing are based on the ability of machines to sense, reason, act, and adapt based on learned experience. They are similar in purpose and divergent in their tendencies in interacting naturally with humans.

In this Special Issue, we will focus on the most recent advancements of the utilization of cognitive computing in biomedicine, including disease diagnostics, biomedical data processing, clinical data analysis, and biomedical research. Within this framework, this Special Issue aims to bring together the latest developments in the area of “Cognitive Computing Paradigms for Medical Big Data Processing and its Trends”. We welcome original research and review articles.

Potential topics include but are not limited to the following:

• Cognitive computing for information retrieval techniques in clinical processing
• Innovative algorithms for cognitive computing frameworks and architecture
• Future improvements in clinical workflow and visual analytics using cognitive computing
• Disease forecasting or prediction in healthcare using cognitive computing
• Cognitive computing trends in biomedical healthcare data analysis
• Diagnosis and medicine follow-up plans management
• High dimensionality of big data in health care
• Prediction of disease using cognitive computing
• Medicine big data analytics
• Medical image processing
• Wearable wireless sensor networks
• Smart wearable body sensors
• Cognitive computing in Internet of Health Things
• Cognitive computing in remote disease monitoring