2024
DOI: 10.1186/s12940-023-01041-3
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Quantitative association between lead exposure and amyotrophic lateral sclerosis: a Bayesian network-based predictive study

Wenxiu Yu,
Fangfang Yu,
Mao Li
et al.

Abstract: Background Environmental lead (Pb) exposure have been suggested as a causative factor for amyotrophic lateral sclerosis (ALS). However, the role of Pb content of human body in ALS outcomes has not been quantified clearly. The purpose of this study was to apply Bayesian networks to forecast the risk of Pb exposure on the disease occurrence. Methods We retrospectively collected medical records of ALS inpatients who underwent blood Pb testing, while m… Show more

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“…The Naive Bayes (NB) model is a widely used binary classifier in machine learning derived from the Bayesian theorem, which assumes that the feature conditions are mutually independent. 24 Using the provided training set, it calculates the joint probability distribution from the input to the output, given the independence of feature words as a premise. Based on this learned model, given input X, it identifies the output Y that maximizes a posteriori probability.…”
Section: Methodsmentioning
confidence: 99%
“…The Naive Bayes (NB) model is a widely used binary classifier in machine learning derived from the Bayesian theorem, which assumes that the feature conditions are mutually independent. 24 Using the provided training set, it calculates the joint probability distribution from the input to the output, given the independence of feature words as a premise. Based on this learned model, given input X, it identifies the output Y that maximizes a posteriori probability.…”
Section: Methodsmentioning
confidence: 99%