Oral cancer causes more than 300'000 new cases and over 140'000 deaths every year globally. It can be categorized into several subtypes, including malignant tumors in the oral cavity, malignant tumors on the lips, and the oropharynx. Therefore, capturing oral cancer images to understand the cancer progression and its biomarker distribution is an important issue. In recent years, various scanning probe techniques have attracted considerable attention, such as electrochemical microscopy (SECM), scanning ion conductance microscopy (SICM), and atomic force microscopy (AFM). Moreover, scanning probe techniques combined with optical images can offer more information that allows scientists to understand chemical reactions during the catalytic processes and kinetics of certain chemical reactions. Nevertheless, the quality of SECM images usually depends on the electrode sizes of the electrodes and many uncontrollable factors. For example, manipulating the fragile glass ultramicroelectrodes and blurred images sometimes frustrates researchers. Usually, scientists tend to fabricate smaller electrode probes to achieve better resolution, but the image speed will be slower, and the fabrication processes are tedious. To overcome the challenges of modern SECM, we improved the electrochemical imaging by using novel soft probes scanned in contact mode and then established the algorithm-assisted artificial intelligence (AI) for image fusion. Firstly, we developed new ultrathin gold wire electrodes with extreme flexibility. The probes were made of gold wire, and sealed in parafilm and polyimide (PI) membrane. Subsequently, the oral cancer biomarkers EGFR protein on the tumor slices were labeled with primary and secondary antibodies with horseradish oxidase (HRP). HRP catalyzed the oxidation reaction of ferrocenmethanol (FcMeOH) to FcMeOH + in the presence of FcMeOH and H2O2. When the probe was scanned over the location of biomarkers, the currents would increase due to the reduction of the FcMeOH + on the electrode surface and thus, generating an SECM image according to the current recorded at different locations on the sample surface. Afterward, the electrochemical images were merged with optical microscopic images to enhance the quality of the SECM images. The merged images have clear tissue boundaries and provide information on the distribution of cancer biomarkers in oral cancer from different human body. However, by changing the parameters of the image fusion process, thousands of fused images were generated, which was confusing and annoying to the researchers.