Healthcare is one of the important areas among concerned researchers in all countries. One of the major transformations that distinguish the era of our life is the greater availability of data, sometimes unstructured and unlabelled. The Healthcare industry can leverage the difficulties and advancement of cognitive technologies, machine learning, and artificial intelligence for solving real-life automation problems. Cognitive computer systems handle substantial volumes of data, potentially improving the quality of medical care to answer inquiries and to bespoke sparing analyses. Evolution in cognitive technology and artificial intelligence improves customer service, guidance, and population health.

Recent covid times have shown us the importance of quality health care infrastructure. The fusion of cognitive computing and artificial intelligence can help us to improve our health care in various ways such as better understanding of the population, patient needs, cost-effective, personalized medicine, clinical needs, analyzing genomic data, physician guidance, mobile health apps, wearable sensors, and innovative ways to proper utilize the use of intensive care unit (ICU).The heterogeneity of medical data can lead us to build more specialized cognitive computing and machine learning algorithms to analyze, review, and understand it for specific complex applications. Currently, the utilization of cognitive computing is limited in health care that leads to a massive opportunity to amalgamate machine learning and cognitive computing for health care professionals, so lots of precious time can be saved and the cost-effective precious solution can be found.

This Special Issue welcomes original research and review articles on this topic.

Potential topics include but are not limited to the following:

• Cognition and AI in healthcare
• Machine learning for emotion recognition
• Human-computer Interaction in healthcare
• Resource-constrained cognitive solutions for healthcare
• Personality prediction using biomedical signals
• Cognitive computing and smart machines
• Explainable AI models for health, biology, and medicine
• AI and cognition for precision medicine
• Data mining and knowledge discovery in healthcare
• Solution optimization for healthcare problems
• AI in genomics
• Medical signal and image processing techniques
• Cognition and artificial intelligence for healthcare social networks