Single-cell Classification Based On Label-free High-resolution Optical Data Of Cell Adhesion Kinetics

This article discusses a new method for classifying different types of cells without the need for labeling or invasive procedures. The method utilizes an optical biosensor and deep learning-based classification models to achieve high accuracy in identifying healthy and cancerous cells. The results also provide insights into the biological basis for the classification. This approach has potential applications in cancer research, immune therapy, and regenerative medicine.