@inproceedings{0171b70f8574491c849c7e06a5ec6dd6,
title = "Machine Learning aided Fiber-Optical System for Liver Cancer Diagnosis in Minimally Invasive Surgical Interventions",
abstract = "A flexible fibre optical probe is implemented to record the parameters of the endogenous fluorescence during minimally invasive interventions in patients with cancers of hepatoduodenal area. Using machine learning techniques, the obtained spectra are classified to indicate cancerous or healthy tissue. For this, a set of different binary classifiers has been trained and tested. The classifiers showing best performance for this task are identified.",
author = "E. Zherebtsov and M. Zajnulina and K. Kandurova and V. Dremin and A. Mamoshin and E. Potapova and S. Sokolovski and A. Dunaev and E.U. Rafailov",
year = "2020",
month = dec,
day = "15",
doi = "10.1109/ICLO48556.2020.9285445",
language = "English",
isbn = "978-1-7281-5232-5",
series = "2020 International Conference Laser Optics (ICLO)",
publisher = "IEEE",
booktitle = "Proceedings - International Conference Laser Optics 2020, ICLO 2020",
address = "United States",
note = "2020 International Conference Laser Optics (ICLO) ; Conference date: 02-11-2020 Through 06-11-2020",
}