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--- confs_page:seaker_list [2021/06/10 11:45]
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+++ confs_page:seaker_list [2021/06/14 15:41]
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-====== SPEAKERS ======
+z====== SPEAKERS ======
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 Abstract:  \\
-Fueled by the ever-increasing amount of data generated by the healthcare system applications for artificial intelligence in healthcare, especially within diagnostic imaging, are rapidly proliferating. Currently, no well-defined framework exists for determining how great ideas for AI algorithms in healthcare will advance from development to integrated clinical practice. Healthcare stakeholders including physicians, patients, medical societies, hospital systems, software developers, the health information technology industry and governmental regulatory agencies all comprise a community that will need to function as an ecosystem system in order for AI algorithms to be deployed, monitored, and improved in widespread clinical practice. Radiologists can play an important role in promoting this AI ecosystem by delineating structured AI use cases for diagnostic imaging and standardizing data elements and workflow integration interfaces. By developing structured AI use cases based on the needs of the physician community, radiologists and radiology specialty societies can assist developers in creating the tools that will advance the practice of medicine. If these use cases specify how datasets for algorithm training, testing and validation can be developed as well as specifying parameters for clinical integration and pathways for assessing algorithm performance in clinical practice, the likelihood of bringing safe and effective algorithms to clinical practice will increase dramatically. The development of an active AI ecosystem will facilitate the development and deployment of AI tools for healthcare that will help physicians solve medicine’s important problems.
+Fueled by the ever-increasing amount of data generated by the healthcare system applications for artificial intelligence in healthcare, especially within diagnostic imaging, are rapidly proliferating. Currently, no well-defined framework exists for determining how great ideas for AI algorithms in healthcare will advance from development to integrated clinical practice. Healthcare stakeholders including physicians, patients, medical societies, hospital systems, software developers, the health information technology industry and governmental regulatory agencies all comprise a community that will need to function as an ecosystem system in order for AI algorithms to be deployed, monitored, and improved in widespread clinical practice. Radiologists can play an important role in promoting this AI ecosystem by delineating structured AI use cases for diagnostic imaging and standardizing data elements and workflow integration interfaces. By developing structured AI use cases based on the needs of the physician community, radiologists and radiology specialty societies can assist developers in creating the tools that will advance the practice of medicine. If these use cases specify how datasets for algorithm training, testing and validation can be developed as well as specifying parameters for clinical integration and pathways for assessing algorithm performance in clinical practice, the likelihood of bringing safe and effective algorithms to clinical practice will increase dramatically. The development of an active AI ecosystem will facilitate the development and deployment of AI tools for healthcare that will help physicians solve medicine’s important problems.  \\    \\    \\    \\
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