Professor Hsiang-Chen Wang is currently a professor at the Department of Mechanical Engineering, and the Institute of Opto-Mechatronics Engineering, National Chung Cheng University (CCU). At the same time, he serves as  the director of the Innovation Incubation Center at CCU; He is also an adjunct professor at the Department of Post Baccalaureate Medicine, Kaohsiung Medical University.

Most of the computer-aided diagnosis (CAD) models developed in the recent years use only RGB images which has only three different color bands. One of the advanced non-invasive techniques used in clinical research is hyperspectral imaging (HSI), which captures data across hundreds of narrow, contiguous bands, each representing a distinct portion of the electromagnetic spectrum. This allows for detailed analysis of tissue characteristics, making HSI a powerful tool in medical diagnostics. This project will utilize various machine learning models, including YOLOv5, YOLOv8, R-CNN, Faster R-CNN etc, to detect and CNN, SVM and Random forest etc for multiple biomedical applications. It will make use of two models of the white-light images (WLI) model and the hyperspectral narrowband images (HSI-NBI) model. These models will be generated through a conversion algorithm referred to as the spectrum-aided vision enhancer (SAVE). The main goal will be to discover early stage bio-markers for effective prognosis. The evaluation of model performance will be conducted using the created confusion matrix and five important indicators: precision, recall, F1-score, mAP, and the confusion matrix of the trained model.