  Cancer is one of the leading causes of death worldwide. Fast and safe
early-stage, pre- and intra-operative diagnostics can significantly contribute
to successful cancer identification and treatment. Artificial intelligence has
played an increasing role in the enhancement of cancer diagnostics techniques
in the last 15 years. This review covers the advances of artificial
intelligence applications in well-established techniques such as MRI and CT.
Also, it shows its high potential in combination with optical
spectroscopy-based approaches that are under development for mobile,
ultra-fast, and low-invasive diagnostics. I will show how spectroscopy-based
approaches can reduce the time of tissue preparation for pathological analysis
by making thin-slicing or haematoxylin-and-eosin staining obsolete. I will
present examples of spectroscopic tools for fast and low-invasive ex- and
in-vivo tissue classification for the determination of a tumour and its
boundaries. Also, I will discuss that, contrary to MRI and CT, spectroscopic
measurements do not require the administration of chemical agents to enhance
the quality of cancer imaging which contributes to the development of more
secure diagnostic methods. Overall, we will see that the combination of
spectroscopy and artificial intelligence constitutes a highly promising and
fast-developing field of medical technology that will soon augment available
cancer diagnostic methods.
