How to re-train a model from false positives
In most cases, one shouldn't retrain a trained network with only the new data. Rather, train the network from scratch with the new and old data. 

Adding new data and retraining the model just on that new set of data, will probably make your model fit to only that new data, thus forgetting general features from the other data it was trained on. 

Also, instead of selecting your final model based on only validation loss, you should select your model based on a validation metric. For example, in your case, it could be accuracy, precision, recall etc