The cultivation of supply side data science in medical imaging: an opportunity to define the future of global health.

The imaging field has more advanced data processing forefronts now, but this experience offers insight from one of our fields' first forays into data science translation, and it exemplifies the promise of data science: the concept of doing more with the data you have. As new landscapes of opportunit...

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Publicado en:European Journal of Nuclear Medicine & Molecular Imaging Vol. 49; no. 2; pp. 436 - 443
Autor principal: Kesner, Adam
Formato: editorial Journal Article
Publicado: Springer Nature Jan2022
Acceso en línea:Ver este registro en EBSCOhost
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        atl: The cultivation of supply side data science in medical imaging: an opportunity to define the future of global health.
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        au: Kesner, Adam
        affil: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1250 First Avenue, Room S-1119E (Box 84), 10065, New York, NY, USA
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          Data Science
          Diagnostic Imaging Psychosocial Factors
          World Health
          Serial Publications
          Diffusion of Innovation
          Storytelling
          Nuclear Medicine
      ab: The imaging field has more advanced data processing forefronts now, but this experience offers insight from one of our fields' first forays into data science translation, and it exemplifies the promise of data science: the concept of doing more with the data you have. As new landscapes of opportunity for data-driven innovation open, we can lead by becoming stewards of imaging data, opening access to its highest fidelity embodiment, and promoting principles of accessibility and free market competition in the data use space. The imaging data-centric moonshot for global health may look like this: In 20 years, we will (a) expand access to imaging by a factor of 10, (b) witness > 100 startup companies utilizing raw medical image data come to fruition, and (c) deliver care to > 1 million nuclear medicine patients using AI networks trained with > 1 million data sets (d) throughout > 100 countries.
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