Dear Colleagues,

Healthcare data analysis has emerged as one of the most promising research areas in recent times. Healthcare data come in various formats, such as clinical data, sensor data, and omics data. Clinical data usually include electronic health records (HERs) comprising laboratory results, radiology images, and so on. Sensor data are recorded from various wireless and wearable sensor devices. Omics data include a huge amount of complex and high dimensional data generally used in bioinformatics, such as genomic data. Effective analysis of healthcare data requires robust techniques to extract relevant features for enhanced diagnosis and prediction of diseases. Artificial Intelligence (AI), in particular, deep learning techniques have brought radical changes to the field of data analysis in healthcare, especially in medical image analysis. Hence, deep learning-based healthcare data analysis systems are becoming increasingly popular and are being widely adopted by health practitioners.

The object of this Special Issue is to report high-quality research on recent advancements in deep learning for healthcare data analysis. Priority will be given to studies that focus on analyzing a variety of medical imaging and sensor data and developing deep-learning-based fusion techniques such as multimodal data fusion, feature fusion, and so on. Researchers are encouraged to report their original previously unpublished work in the following topics.

Potential topics appropriate for this Special Issue include (but are not restricted to):

• Deep-learning-based healthcare data analysis;
• Deep learning models for multimodal healthcare data fusion;
• Feature fusion for smart healthcare systems;
• Advanced methodologies for effective diagnosis of infectious disease;
• Deep-learning-based health monitoring systems to monitor and track casualties of various health disorders;
• Healthcare sensor data fusion for smart healthcare monitoring;
• Deep-learning-based medical image classification and segmentation;
• Advanced machine learning for various disease predictions.

Prof. Dr. Nargis Khan
Prof. Dr. Lutful Karim
Guest Editors

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