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Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital

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0 upcoming talks and 2 talks in the archive.

Cambridge AI in Medicine Seminar Series

AI in Medical Imaging Research Seminar – Nikita Sushentsev – "Time-series Radiomics: top or flop? - A new framework for longitudinal medical image analysis"

User Nikita Sushentsev, Gates Scholar and PhD student at the Department of Radiology, University of Cambridge.

House Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital.

Tuesday 25 October 2022, 10:00-11:00

Cambridge AI in Medicine Seminar Series

AI in Medical Imaging Research Seminar – Cathal McCague – "Stop rolling the DSC! - A new framework for assessing the clinical utility of segmentation algorithms"

User Cathal McCague, Department of Radiology.

House Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital.

Tuesday 27 September 2022, 10:00-11:00

Please see above for contact details for this list.

Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital

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Cambridge AI in Medicine Seminar Series

AI in Medical Imaging Research Seminar – Nikita Sushentsev – "Time-series Radiomics: top or flop? - A new framework for longitudinal medical image analysis"

👤 Nikita Sushentsev, Gates Scholar and PhD student at the Department of Radiology, University of Cambridge 📅 Tuesday 25 October 2022, 10:00-11:00 📍 Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital

Cambridge AI in Medicine Seminar Series

AI in Medical Imaging Research Seminar – Cathal McCague – "Stop rolling the DSC! - A new framework for assessing the clinical utility of segmentation algorithms"

👤 Cathal McCague, Department of Radiology 📅 Tuesday 27 September 2022, 10:00-11:00 📍 Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital

Please see above for contact details for this list.

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Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital

AI in Medical Imaging Research Seminar – Nikita Sushentsev – "Time-series Radiomics: top or flop? - A new framework for longitudinal medical image analysis"

AI in Medical Imaging Research Seminar – Cathal McCague – "Stop rolling the DSC! - A new framework for assessing the clinical utility of segmentation algorithms"

Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital

AI in Medical Imaging Research Seminar – Nikita Sushentsev – "Time-series Radiomics: top or flop? - A new framework for longitudinal medical image analysis"

AI in Medical Imaging Research Seminar – Cathal McCague – "Stop rolling the DSC! - A new framework for assessing the clinical utility of segmentation algorithms"

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Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital

AI in Medical Imaging Research Seminar – Nikita Sushentsev – &quot;Time-series Radiomics: top or flop? - A new framework for longitudinal medical image analysis&quot;

AI in Medical Imaging Research Seminar – Cathal McCague – &quot;Stop rolling the DSC! - A new framework for assessing the clinical utility of segmentation algorithms&quot;

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Berridge room on L5 at the Department of Radiology, Addenbrooke's hospital

AI in Medical Imaging Research Seminar – Nikita Sushentsev – &quot;Time-series Radiomics: top or flop? - A new framework for longitudinal medical image analysis&quot;

AI in Medical Imaging Research Seminar – Cathal McCague – &quot;Stop rolling the DSC! - A new framework for assessing the clinical utility of segmentation algorithms&quot;

AI in Medical Imaging Research Seminar – Nikita Sushentsev – "Time-series Radiomics: top or flop? - A new framework for longitudinal medical image analysis"

AI in Medical Imaging Research Seminar – Cathal McCague – "Stop rolling the DSC! - A new framework for assessing the clinical utility of segmentation algorithms"

AI in Medical Imaging Research Seminar – Nikita Sushentsev – "Time-series Radiomics: top or flop? - A new framework for longitudinal medical image analysis"

AI in Medical Imaging Research Seminar – Cathal McCague – "Stop rolling the DSC! - A new framework for assessing the clinical utility of segmentation algorithms"