Figure 8 utilizes the raw data from Figure 7 without the logarithmic scale. This illustration offers the advantages of intuitive comprehension and potential integration with machine learning techniques for intelligent VEGF detection, in which the real and imaginary impedance values of the Nyquist plot can be arranged to be the feature vector of the machine-learning classifier. Such a machine-learning-based approach was adopted in article [28] for the development of an impedimetric immunosensor on the detection of endometriosis. The gene discussed is VEGFA; the disease is endometriosis.