Detecting Patient Health Trajectories Using a Full-Body Burn Physiology Model
A whole-body physiology model of inflammatory burn injury was used to train an algorithm to correctly detect patients’ states. The physiology model of a thermal injury takes the surface area of patient skin burned as an input to the model and responds to common treatments. This model is leveraged to...
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Veröffentlicht in: | BioMedInformatics 2021-12, Vol.1 (3), p.127-137 |
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creator | Baird, Austin Amos-Binks, Adam Tatum, Nathan White, Steven Hackett, Matthew Serio-Melvin, Maria |
description | A whole-body physiology model of inflammatory burn injury was used to train an algorithm to correctly detect patients’ states. The physiology model of a thermal injury takes the surface area of patient skin burned as an input to the model and responds to common treatments. This model is leveraged to build a database of patient physiology as a function of total body surface area burn, without treatment, over a 48-h window. Using this database, we train a model to determine patient injury status as a function of the available physiology data. The algorithm can group virtual patients into three distinct categories, corresponding to long term patient health. The results show that, given an initial virtual patient and injury, the algorithm can correctly determine the placement of that patient into the corresponding category, effectively classifying long term patient outcomes. |
doi_str_mv | 10.3390/biomedinformatics1030009 |
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The physiology model of a thermal injury takes the surface area of patient skin burned as an input to the model and responds to common treatments. This model is leveraged to build a database of patient physiology as a function of total body surface area burn, without treatment, over a 48-h window. Using this database, we train a model to determine patient injury status as a function of the available physiology data. The algorithm can group virtual patients into three distinct categories, corresponding to long term patient health. 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The physiology model of a thermal injury takes the surface area of patient skin burned as an input to the model and responds to common treatments. This model is leveraged to build a database of patient physiology as a function of total body surface area burn, without treatment, over a 48-h window. Using this database, we train a model to determine patient injury status as a function of the available physiology data. The algorithm can group virtual patients into three distinct categories, corresponding to long term patient health. The results show that, given an initial virtual patient and injury, the algorithm can correctly determine the placement of that patient into the corresponding category, effectively classifying long term patient outcomes.</abstract><doi>10.3390/biomedinformatics1030009</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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title | Detecting Patient Health Trajectories Using a Full-Body Burn Physiology Model |
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