Bayesian networks in biomedicine and health-care

By Peter J.F. Lucas, L. V. D. Gaag, Ameen Abu-Hanna. Artif. Intell. Medicine, 2004

373 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Information Management

View Paper: https://www.semanticscholar.org/paper/c9e62ffb14bf832534ab56572cb155b08f3b9edf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Michael S. Steinbach
2. Vipin Kumar
3. Ignavier Ng
4. Zhuangyan Fang
5. J. Ramon
6. Shengyu Zhu
7. György J. Simon
8. Zhitang Chen

In Health Information Management

1. Michael S. Steinbach
2. Vipin Kumar
3. György J. Simon
4. Pranjul Yadav

Citations in the corpus

• Mining Electronic Health Records: A Survey (2017, methodology): “…have also been used to model EHRs for diagnostic reasoning (constructing the medical state of the patient using laboratory test results), prognostic reasoning (prediction about the future) and discovering functional static interactions between the outcome and the predictors [Lucas et al. 2004].”
• Masked Gradient-Based Causal Structure Learning (2019, background): “, 1996), biomedicine and heathcare (Lucas et al., 2004), and biology (Sachs et al.”
• Machine learning techniques to examine large patient databases. (2009, background): “A survey of Bayesian Networks applied in health care can be found in the article of Lucas et al. 58 Ramon et al 14 repeated the same experiment from Fig.”