1 code implementation • 26 Feb 2023 • Chihcheng Hsieh, Isabel Blanco Nobre, Sandra Costa Sousa, Chun Ouyang, Margot Brereton, Jacinto C. Nascimento, Joaquim Jorge, Catarina Moreira
In this work, we propose a novel architecture consisting of two fusion methods that enable the model to simultaneously process patients' clinical data (structured data) and chest X-rays (image data).
no code implementations • 6 Feb 2023 • André Luís, Chihcheng Hsieh, Isabel Blanco Nobre, Sandra Costa Sousa, Anderson Maciel, Catarina Moreira, Joaquim Jorge
This paper proposes a novel multimodal DL architecture incorporating medical images and eye-tracking data for abnormality detection in chest x-rays.
1 code implementation • 4 Mar 2022 • Catarina Moreira, Yu-Liang Chou, Chihcheng Hsieh, Chun Ouyang, Joaquim Jorge, João Madeiras Pereira
This study investigates the impact of machine learning models on the generation of counterfactual explanations by conducting a benchmark evaluation over three different types of models: decision-tree (fully transparent, interpretable, white-box model), a random forest (a semi-interpretable, grey-box model), and a neural network (a fully opaque, black-box model).
no code implementations • 19 Jul 2021 • Chihcheng Hsieh, Catarina Moreira, Chun Ouyang
We design an extension of DiCE, namely DiCE4EL (DiCE for Event Logs), that can generate counterfactual explanations for process prediction, and propose an approach that supports deriving milestone-aware counterfactual explanations at key intermediate stages along process execution to promote interpretability.