31 datascEYEnce! Computer Vision News Computer Vision News GoDARTS a longitudinal cohort. Such rich data has been instrumental in augmenting diabetic management and commercialising tools like “myDiabetes.” What kind of exciting results did you encompass and what are some future directions? One of the most exciting details of his work is that retinal images and genome data are rather uncorrelated and hence combining them, adds a lot of information to cardiovascular disease understanding and diagnosis. With these words, he highlighted the importance of multi-modality. Looking ahead, Emanuele is exploring the time dimension in his research. By analysing the history of retinal images using techniques like LSTM, time series genetic algorithms, and transformers, his team aims to provide a more comprehensive understanding of these diseases. And finally, what are the main challenges or limitations you have encountered during your research? Of course, I didn’t only want to hear the positive parts of the research because it is not always rainbows and butterflies! Emanuele sees a range of limitations, especially in computational cost. It is currently unfeasible for many labs to access or afford an environment for experiments. Therefore research for computationally more efficient large models is needed. Another limitation is the collection and preparation of data. It is a lengthy process but is of great importance since the accuracy and robustness of a neural network are dependent on the amount and variety of data it has been trained on. I really enjoyed the interview with Emanuele and want to thank him again for telling me about his research and projects. And now, the answer you have all been waiting for! The eye is a window to vascular disease which I personally find quite fascinating as it is very easy to take an image of the retinal vasculature! Doctors have recognised that changes to the tiny blood vessels in the retina are indicators of broader vascular disease, including problems with the heart, diabetic vascular diseases, and vascular dementia. Computer Vision News Publisher: RSIP Vision Copyright: RSIP Vision Editor: Ralph Anzarouth All rights reserved Unauthorized reproduction is strictly forbidden. Our editorial choices are fully independent from IEEE, CVPR and all conference organizers.
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