Discovery of aggressive cancer cell types by Vanderbilt researchers made possible with machine learning techniques

Good news! This is still only the beginning of applying machine learning to analyse and improve cancer diagnostics.



"By applying unsupervised and automated machine learning techniques to the analysis of millions of cancer cells, [researchers] have identified new cancer cell types in [glioblastoma] brain tumors. ... developed Risk Assessment Population IDentification (RAPID), an open-source machine learning algorithm that revealed coordinated patterns of protein expression and modification associated with survival outcomes. ... “One of the most exciting results of our research is that unsupervised machine learning found the worst offender cells without needing the researchers to give it clinical or biological knowledge as context,” ... The researchers’ machine learning analysis enabled their team to study multiple characteristics of the proteins in brain tumor cells in relation to other characteristics, delivering new and unexpected patterns. ..."



Discovery of aggressive cancer cell types by Vanderbilt researchers made possible with machine learning techniques | Vanderbilt News | Vanderbilt University