Scientists in a recent study are developing a unique way to identify chemical fingerprints for different of breast cancers. The team of researchers from Lancaster University, in partnership with Airedale NHS Foundation Trust, are working on a specialized chemical analytical technique on biopsies called Raman Spectroscopy. This technique is expected to help in identifying the molecular structure of different breast cancers and its variations.
The chemical footprints will be used to train AI software, which will create a new tool to accurately diagnose breast cancers. The results generated through this study were published in the journal Expert Review of Molecular Diagnostics.
The analysis by Raman was able to provide real-time information on cells. This information was used to check the behavior, spread, and emerging of the cells elsewhere in the body. Once it is identified through the fingerprints of breast cancer cells the researchers were able to observing the changes in it. This helped them identify four sub-types of cancer by complex algorithms.
According to the reports, in the next stage of the research, they will be looking at databases of chemical structures of different types of breast cancer cells and the different forms it can take. The generated databases will then be used to train algorithms to AI through machine learning. The new algorithms are promising quicker diagnosis through rapid information to medical specialists.