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Cancer is one of the leading causes of death worldwide. Fast and safeearly-stage, pre- and intra-operative diagnostics can significantly contributeto successful cancer identification and treatment. Artificial intelligence hasplayed an increasing role in the enhancement of cancer diagnostics techniquesin the last 15 years. This review covers the advances of artificialintelligence applications in well-established techniques such as MRI and CT.Also, it shows its high potential in combination with opticalspectroscopy-based approaches that are under development for mobile,ultra-fast, and low-invasive diagnostics. I will show how spectroscopy-basedapproaches can reduce the time of tissue preparation for pathological analysisby making thin-slicing or haematoxylin-and-eosin staining obsolete. I willpresent examples of spectroscopic tools for fast and low-invasive ex- andin-vivo tissue classification for the determination of a tumour and itsboundaries. Also, I will discuss that, contrary to MRI and CT, spectroscopicmeasurements do not require the administration of chemical agents to enhancethe quality of cancer imaging which contributes to the development of moresecure diagnostic methods. Overall, we will see that the combination ofspectroscopy and artificial intelligence constitutes a highly promising andfast-developing field of medical technology that will soon augment availablecancer diagnostic methods.

Advances of Artificial Intelligence in Classical and Novel Spectroscopy-Based Approaches for Cancer Diagnostics. A Review