UniHPF : Universal Healthcare Predictive Framework with Zero Domain Knowledge
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arXiv
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| Hauptverfasser: | , , , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2022
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| _version_ | 1866909301638955008 |
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| author | Hur, Kyunghoon Oh, Jungwoo Kim, Junu Kim, Jiyoun Lee, Min Jae Cho, Eunbyeol Moon, Seong-Eun Kim, Young-Hak Choi, Edward |
| author_facet | Hur, Kyunghoon Oh, Jungwoo Kim, Junu Kim, Jiyoun Lee, Min Jae Cho, Eunbyeol Moon, Seong-Eun Kim, Young-Hak Choi, Edward |
| contents | Despite the abundance of Electronic Healthcare Records (EHR), its heterogeneity restricts the utilization of medical data in building predictive models. To address this challenge, we propose Universal Healthcare Predictive Framework (UniHPF), which requires no medical domain knowledge and minimal pre-processing for multiple prediction tasks. Experimental results demonstrate that UniHPF is capable of building large-scale EHR models that can process any form of medical data from distinct EHR systems. We believe that our findings can provide helpful insights for further research on the multi-source learning of EHRs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2211_08082 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | UniHPF : Universal Healthcare Predictive Framework with Zero Domain Knowledge Hur, Kyunghoon Oh, Jungwoo Kim, Junu Kim, Jiyoun Lee, Min Jae Cho, Eunbyeol Moon, Seong-Eun Kim, Young-Hak Choi, Edward Machine Learning Neural and Evolutionary Computing Despite the abundance of Electronic Healthcare Records (EHR), its heterogeneity restricts the utilization of medical data in building predictive models. To address this challenge, we propose Universal Healthcare Predictive Framework (UniHPF), which requires no medical domain knowledge and minimal pre-processing for multiple prediction tasks. Experimental results demonstrate that UniHPF is capable of building large-scale EHR models that can process any form of medical data from distinct EHR systems. We believe that our findings can provide helpful insights for further research on the multi-source learning of EHRs. |
| title | UniHPF : Universal Healthcare Predictive Framework with Zero Domain Knowledge |
| topic | Machine Learning Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2211.08082 |