Indu Ilanchezian

Indu Ilanchezian
Indu Ilanchezian was a Ph.D. student in the Department of Data Science at the Hertie Institute for AI in Brain Health at the University of Tübingen and an IMPRS-IS scholar. Her research objective was to develop interpretable deep learning models for clinical diagnostic applications in ophthalmology. Her research was particularly focused on inherently interpretable models and visual counterfactual explanations. Besides interpretability, she was interested in generative models, diffusion models and adversarially robust models. Indu finished her PhD in 2023.
To harness the power of AI in real world clinical situations, an explanation of their decisions is of utmost importance.
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Boreiko, V., Ilanchezian, I., Ayhan, M. S., Müller, S., Koch, L. M., Faber, H., Berens, P. & Hein, M.

Visual explanations for the detection of diabetic retinopathy from retinal fundus images

Feb 02, 2022 | International conference on medical image computing and computer-assisted intervention (MICCAI) (pp. 539-549), Cham: Springer Nature Switzerland
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Ilanchezian, I., Kobak, D., Faber, H., Ziemssen, F., Berens, P., & Ayhan, M. S

Interpretable gender classification from retinal fundus images using BagNets.

Sep 21, 2021 | Proceedings, Part III 24 (pp. 477-487). Springer International Publishing.