DHM uses a coherent light source (laser) that illuminates the sample composed of cells and the medium in which the cells are suspended. The light scattered from the cells and the medium interfere with one another. The interference pattern is called a digital hologram, which is recorded by the instrument in the digital camera (Fig.1). After specific digital processing, a Digital Holographic Microscopy (DHM) can be reconstructed (like conventional brightfield microscopy images, with the main difference that it shows the refractive index of the sample, instead of the absorbance). Due to the low light intensity of the DHM laser, the cellular analysis can be performed without impacting the cells’ status. Using optimized numerical algorithms, pairing DHM with machine learning (ML) allows further study of the obtained image. The “intelligent” analysis extracts detailed information about morphology or cell structure, enabling viability recognition without the need for staining. This is a distinct advantage over traditional methods, which not only have the potential to alter the sample integrity but can also be time-consuming, error-prone, and subject to intra-user variability.