About this Research Topic
With the latest advancements in Artificial intelligence (AI), it has reshaped the way how industry sectors perform their business operations. The health care industry has been no exception and has shown monumental advancements in the areas of diagnosis including, cancer diagnosis, triage of crucial findings, identification of acute abnormalities, support for radiologists in prioritising cases involving life-threatening conditions, diagnosis of cardiac arrhythmias, prediction of stroke outcomes, and management of chronic diseases. The sector has benefitted from innovative telehealth serves and robust record management, which helps in maintain volumes of data centrally that is readily available.
This Research Topic aims to provide a platform for researchers to disseminate cutting-edge research that investigates and explores the potential of artificial intelligence technologies in healthcare sector with a focus on computer vision, deep learning, machine learning, medical imaging, sensor data, and clinical data analysis. The research topic will enable researchers to collaborate globally and investigate the challenges of employing artificial intelligence, while considering privacy and security, and ethical implications in the healthcare sector. This collection aims to demonstrate how AI can significantly improve patient outcomes, therapy personalization, and diagnostic accuracy by engaging recent developments in deep learning, machine learning, medical imaging, and sensor data analysis. Moreover, it caters for novelty in healthcare focusing on AI applications and approaches. Furthermore, novel theoretical contributions based on fundamental, general topics related to medical imaging, healthcare, medical diagnosis are encouraged for submission.
This Research Topic encourages submissions that address a wide range of themes, within the scope of AI in healthcare sector, including (but not limited to):
• AI algorithms for medical imaging
• AI based medical diagnostics systems
• Machine learning and deep learning for medical imaging
• Wearable health applications
• Computational pathology
• Whole slide image analysis using AI
• Applications of sensor data analysis using AI in patient monitoring
• Advances in computer vision for medical applications
This Research Topic aims to provide a platform for researchers to disseminate cutting-edge research that investigates and explores the potential of artificial intelligence technologies in healthcare sector with a focus on computer vision, deep learning, machine learning, medical imaging, sensor data, and clinical data analysis. The research topic will enable researchers to collaborate globally and investigate the challenges of employing artificial intelligence, while considering privacy and security, and ethical implications in the healthcare sector. This collection aims to demonstrate how AI can significantly improve patient outcomes, therapy personalization, and diagnostic accuracy by engaging recent developments in deep learning, machine learning, medical imaging, and sensor data analysis. Moreover, it caters for novelty in healthcare focusing on AI applications and approaches. Furthermore, novel theoretical contributions based on fundamental, general topics related to medical imaging, healthcare, medical diagnosis are encouraged for submission.
This Research Topic encourages submissions that address a wide range of themes, within the scope of AI in healthcare sector, including (but not limited to):
• AI algorithms for medical imaging
• AI based medical diagnostics systems
• Machine learning and deep learning for medical imaging
• Wearable health applications
• Computational pathology
• Whole slide image analysis using AI
• Applications of sensor data analysis using AI in patient monitoring
• Advances in computer vision for medical applications
Keywords: Medical AI, healthcare AI, medical imaging, Sensor data analysis, Computer vision, Deep learning, Machine learning, Weakly supervised learning, Multiple instance learning, Representation learning, Generative models, Clinical data analysis
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
