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AI applications in radiological image analysis for cancer research

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Imaging is one of the main pillars of clinical protocols for cancer care that provides essential non-invasive biomarkers for detection, diagnosis and response assessment. The development of Artificial Intelligence (AI) tools have proven potential to transform the analysis of radiological images, by significantly reducing processing time, by increasing the reproducibility of measurements and by improving the sensitivity of tumour detection compared to the standard visual interpretation, leading to cancer early detection.

Dr Lorena Escudero Sanchez is a particle physicist, with a PhD in neutrino physics, who has worked in large international collaborations for the neutrino oscillation experiments T2K , MicroBooNE and DUNE . She now works on AI applications to radiological image analysis for cancer research, at the Department of Radiology of the University of Cambridge and CRUK Cambridge Centre. She is also a Turing Fellow of The Alan Turing Instittue and a Borysiewicz Interdisciplinary Fellow.

This talk is part of the Data Intensive Science Seminar Series series.

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