Classification of tumor signatures from electrosurgical vapors using mass spectrometry and machine learning: a feasibility study - researchr publication authors

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Laura Connolly, Amoon Jamzad, Martin Kaufmann, Rachel Rubino, Alireza Sedghi, Tamas Ungi, Mark Asselin, Scott Yam, John F. Rudan, Christopher Nicol, Gabor Fichtinger, Parvin Mousavi. Classification of tumor signatures from electrosurgical vapors using mass spectrometry and machine learning: a feasibility study. In Baowei Fei, Cristian A. Linte, editors, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, Houston, TX, USA, February 15-20, 2020. Volume 11315 of SPIE Proceedings, SPIE, 2020. [doi]

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