An AI-powered blood test to detect cancer using nanoDSF
Update: 2020-08-10
Description
Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2020.08.09.242818v1?rss=1
Authors: Tsvetkov, P. O., Eyraud, R., Ayache, S., Bougaev, A. A., Malesinski, S., Benazha, H., Gorokhova, S., Buffat, C., Dehais, C., Sanson, M., Bielle, F., Figarella-Branger, D., Chinot, O., Tabouret, E., Devred, F.
Abstract:
We describe a novel cancer diagnostic method based on plasma denaturation profiles obtained by a non-conventional use of Differential Scanning Fluorimetry. We show that 84 glioma patients and 63 healthy controls can be automatically classified using denaturation profiles with the help of machine learning algorithms with 92% accuracy. Proposed high throughput workflow can be applied to any type of cancer and could become a powerful pan-cancer diagnostic and monitoring tool from a simple blood test.
Copy rights belong to original authors. Visit the link for more info
http://biorxiv.org/cgi/content/short/2020.08.09.242818v1?rss=1
Authors: Tsvetkov, P. O., Eyraud, R., Ayache, S., Bougaev, A. A., Malesinski, S., Benazha, H., Gorokhova, S., Buffat, C., Dehais, C., Sanson, M., Bielle, F., Figarella-Branger, D., Chinot, O., Tabouret, E., Devred, F.
Abstract:
We describe a novel cancer diagnostic method based on plasma denaturation profiles obtained by a non-conventional use of Differential Scanning Fluorimetry. We show that 84 glioma patients and 63 healthy controls can be automatically classified using denaturation profiles with the help of machine learning algorithms with 92% accuracy. Proposed high throughput workflow can be applied to any type of cancer and could become a powerful pan-cancer diagnostic and monitoring tool from a simple blood test.
Copy rights belong to original authors. Visit the link for more info
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