Use of machine learning (ML) in the prediction of ATRX and IDH mutation status in glioma

Laura Pigott; Chor Yiu Chloe Chung

Use of machine learning (ML) in the prediction of ATRX and IDH mutation status in glioma

Laura Pigott
, Chor Yiu Chloe Chung

Research output: Contribution to conference › Poster › peer-review

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Abstract

The poster explores a non-invasive and efficient approach to glioma diagnosis and prognosis. Aiming to support clinicians in the process of decision-making and personalised treatment planning.

Original language	English
Publication status	Published - 11 Oct 2024

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CSP_poster_draftFinal published version, 1.06 MBLicence: CC BY 4.0

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title = "Use of machine learning (ML) in the prediction of ATRX and IDH mutation status in glioma",

abstract = "The poster explores a non-invasive and efficient approach to glioma diagnosis and prognosis. Aiming to support clinicians in the process of decision-making and personalised treatment planning. ",

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AU - Chung, Chor Yiu Chloe

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N2 - The poster explores a non-invasive and efficient approach to glioma diagnosis and prognosis. Aiming to support clinicians in the process of decision-making and personalised treatment planning.

AB - The poster explores a non-invasive and efficient approach to glioma diagnosis and prognosis. Aiming to support clinicians in the process of decision-making and personalised treatment planning.

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M3 - Poster

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Use of machine learning (ML) in the prediction of ATRX and IDH mutation status in glioma

Abstract

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