Determining LEAD toxicity in pregnant women using machine learning

Abstract Background and Objective: LEAD, an environmental toxicant, accounts for 0.6% of the global burden of disease, with the highest burden in developing countries. It can permeate through the foetus blood-brain barrier causing a negative impact on foetal growth and the developing brain. Literacy and awareness related to its impact are low and the clinical establishment for biological monitoring of Blood LEAD Level is low, costly, and time-consuming.Methods: We propose a novel approach to build a low-cost point-of-care analytical device, a screening app that can predict LEAD toxicity levels in maternal blood. A computational model is built that learns from maternal data comprising of blood LEAD level and a set of sociodemographic features, and then predicts the LEAD toxicity level based on the set of input features.Results: Following feature selection methods, the 11-feature set obtained from Boruta algorithm gave the best prediction results. The k-Nearest Neighbour-based model gave 94.00% accuracy whereas the Neural Network-based model gave 92.50% accuracy when tested on 200 participants.Conclusion: The range of features identified in the built models can estimate the underlying function and can accurately model LEAD toxicity prediction and provide an understanding of toxicity level. Early identification and intervention of LEAD-exposed pregnant women will reduce LEAD poisoning in infants and thus, prevent harmful effects on health throughout childhood and adulthood. The built prediction model is beneficial in improving the point of care and hence reducing the cost and the risk involved. It is envisaged that the app will become a part of a screening process to assist healthcare experts at the point of evaluating the LEAD toxicity level in pregnant women. Women screened positive could be given a range of facilities including preliminary counselling to being referred to the health centre for further diagnosis. Steps could be taken to reduce maternal exposure and hence, it could also be possible to mitigate infant’s LEAD exposure by reducing transfer from the pregnant woman.