Enhancing Lupus Anticoagulant Testing with Machine Learning: Deep Neural Networks Match Expert Performance without the Need for Feature Selection

The comparable performance of the 4 domain knowledge optimized DNNs and the multioutput DNN using all 13 input features suggests that the DNN may learn feature importance or mapping to a task without explicit input selection. Given its relative simplicity and versatility, the multioutput DNN is the preferred choice for implementation in a clinical laboratory to standardize LAC diagnosis.