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SciBar : Digital Medicine

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Title: Digital Epidemiology: Modelling of Epidemic Spread using Human Mobility Data

Speaker: Dr Eiko Yoneki

Respiratory and other close-contact infectious diseases, such as TB, measles and pneumonia are major killers in much of the developing world. Understanding how the diseases spread and identifying how best to control them can be tackled by mathematically modelling their spread. Although central to the models, few quantitative data are available on relevant contact patterns, and no study to measure these factors has yet been attempted in rural Africa. I will describe a desirable plan of pilot project to collect human mobility data using RFID sensors, Raspberry Pis and mobile-phones, recording proximity, to gather information on human interactions in rural and urban African communities.

Title: Computer Vision and Machine Learning : An application in digital pathology

Speaker: Dr Ali Dariush

Digital pathology is rapidly becoming popular worldwide. It not only helps to understand the nature of the disease through the analysis of tissue-based images but also advances our statistical knowledge of the disease-related factors via high throughput analysis of the imaging data. Here I briefly explain how computer vision and machine learning can help to address some of the key questions in digital pathology.

This talk is part of the SciBar Cambridge series.

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