Radiation Dosimetry, Artificial Intelligence and Digital Twins: Old Dog, New Tricks.

Developments in artificial intelligence, particularly convolutional neural networks and deep learning, have the potential for problem solving that has previously confounded human intelligence. Accurate prediction of radiation dosimetry pre-treatment with scope to adjust dosing for optimal target and...

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Publicado en:Seminars in Nuclear Medicine Vol. 53; no. 3; pp. 457 - 467
Autores principales: Currie, Geoffrey M., Rohren, Eric M.
Formato: review Journal Article
Publicado: W B Saunders May2023
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Radiation Dosimetry, Artificial Intelligence and Digital Twins: Old Dog, New Tricks.
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          Currie, Geoffrey M.
          Rohren, Eric M.
        affil: Charles Sturt University, NSW, Australia
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      ab: Developments in artificial intelligence, particularly convolutional neural networks and deep learning, have the potential for problem solving that has previously confounded human intelligence. Accurate prediction of radiation dosimetry pre-treatment with scope to adjust dosing for optimal target and non-target tissue doses is consistent with striving for improved the outcomes of precision medicine. The combination of artificial intelligence and production of digital twins could provide an avenue for an individualised therapy doses and enhanced outcomes in theranostics. While there are barriers to overcome, the maturity of individual technologies (i.e. radiation dosimetry, artificial intelligence, theranostics and digital twins) places these approaches within reach.
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