Malignant melanoma accounts for about 1–3% of all malignancies in the West, especially in the United States. More than 9000 people die each year. In general, it is difficult to characterize a skin lesion from a photograph. In this paper, we propose a deep learning-based computer-aided diagnostic algorithm for the classification of malignant melanoma and benign skin tumors from RGB channel skin images. The proposed deep learning model constitutes a tumor lesion segmentation model and a classification model of malignant melanoma. First, U-Net was used to classify skin lesions in dermoscopy images. We implement an algorithm to classify malignant melanoma and benign tumors using skin lesion images and expert labeling results from convolutional neural networks. The U-Net model achieved a dice similarity coefficient of 81.1% compared to the expert labeling results. The classification accuracy of malignant melanoma reached 80.06%. As a result, the proposed AI algorithm is expected to be utilized as a computer-aided diagnostic algorithm to help early detection of malignant melanoma.

For electromagnetic induction wireless power transmission using an elliptical receiving coil, we investigated changes in magnetic field distribution and power transmission efficiency due to changes in the position of the transmitting and receiving coils. The simulation results using the high-frequency structure simulator were compared with the actual measurement results. It has been shown that even if the alignment between the transmitting coil and the receiving coil is changed to some extent, the transmission efficiency on the simulator can be maintained relatively stable. The transmission efficiency showed the maximum when the center of the receiving coil was perfectly aligned with the center of the transmitting coil. Although the reduction in efficiency was small when the center of the receiving coil was within ± 10 mm from the center of the transmitting coil, it was found that the efficiency was greatly reduced when the receiving coil deviated by more than 10 mm. Accordingly, it has been found that even if the perfect alignment is not maintained, the performance of the wireless power transmission system is not significantly reduced. When the center of the receiving coil is perfectly aligned with the center of the transmitting coil, the transmission efficiency is maximum, and even if the alignment is slightly changed, the performance of wireless power transmission maintains a certain level. This result proposes a standardized wireless transmission application method in the use of wireless power for implantable sensors.

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