Clinical Reasoning over Tabular Data and Text with Bayesian Networks
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866917673357541376 |
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| author | Rabaey, Paloma Deleu, Johannes Heytens, Stefan Demeester, Thomas |
| author_facet | Rabaey, Paloma Deleu, Johannes Heytens, Stefan Demeester, Thomas |
| contents | Bayesian networks are well-suited for clinical reasoning on tabular data, but are less compatible with natural language data, for which neural networks provide a successful framework. This paper compares and discusses strategies to augment Bayesian networks with neural text representations, both in a generative and discriminative manner. This is illustrated with simulation results for a primary care use case (diagnosis of pneumonia) and discussed in a broader clinical context. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2403_09481 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Clinical Reasoning over Tabular Data and Text with Bayesian Networks Rabaey, Paloma Deleu, Johannes Heytens, Stefan Demeester, Thomas Artificial Intelligence Bayesian networks are well-suited for clinical reasoning on tabular data, but are less compatible with natural language data, for which neural networks provide a successful framework. This paper compares and discusses strategies to augment Bayesian networks with neural text representations, both in a generative and discriminative manner. This is illustrated with simulation results for a primary care use case (diagnosis of pneumonia) and discussed in a broader clinical context. |
| title | Clinical Reasoning over Tabular Data and Text with Bayesian Networks |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2403.09481 |