Biostatistics Group Seminar, Tuesday 14th January

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Biostatistics Group Seminar, Tuesday 14th January

Postby rsc97 » Sat Dec 21, 2019 11:15 pm

Biostatistics Group Seminar
School of Primary, Community and Social Care
Keele University

Title: Statistical spatial modelling vs machine learning: on detection of diseases from ophthalmic images

Speaker: Dr Gabriela Czanner, Department of Applied Mathematics, Liverpool John Moores University

Date: Tuesday 14th January 12:00-13:00

Venue: Dinwoodie Lecture Theatre, David Weatherall Building


Abstract: Images are an essential part of medical research, diagnosis, screening and monitoring of diseases. For example, the capillary non-perfusion lesions in images of retina can aid to understand the aetiology of malaria and the shape of optic disc can help to diagnose glaucoma. Often a clinician would manually evaluate these temporal or imaging data, however this is a complex task for a human observer, it is therefore expensive in terms of time and human training, it is subjective and there is a risk that potentially important information is being disregarded. A key to interpret the imaging and temporal data is to create and employ efficient quantitative approaches. This is a growing area of research in statistics, machine learning and computer vision. We have developed spatial statistical modelling approaches to tackle this challenge. Our model is based on hierarchical statistical modelling, it involves spatial correlations and we use empirical Bayes to calculate posterior probability of the disease category. In retinal images we showed that retinal capillary-nonperfusion is more common in patients who died from malaria, and we demonstrated that the shape of the optic nerve can diagnose glaucoma with a supreme data efficiency and with a high accuracy comparable to machine learning approaches.
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