WideHealth Seminars with Cátia Pesquita, "Knowledge Science for trust in AI-based biomedical and clinical applications"

This podcast is part of the "WideHealth Seminars". This project (widehealth.eu) has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952279  

Speaker: Cátia Pesquita 

Title: Knowledge Science for trust in AI-based biomedical and clinical applications   

Abstract: 

Biomedical and clinical applications of artificial intelligence are increasingly popular in the scientific community. However, concerns about potential bias and the lack of explainability of high-performing machine learning methods such as deep learning are limiting their adoption in practice. In this talk I explain what knowledge science is and why it is key to assess the trustworthiness of biomedical data and AI outcomes. In particular, I discuss three contexts, data, domain and user, and draw on specific examples to illustrate pitfalls and how knowledge science can overcome them.   

Short bio:  

Catia Pesquita is an Assistant Professor in Computer Science at Faculdade de Ciências da Universidade de Lisboa and a Senior Researcher at LASIGE where she leads the Health and Bioinformatics Research Line of Excellence. She has a multidisciplinary background in Biology and Computer Science, and she develops her research at the intersection between the areas of Knowledge Representation and Data Mining, with a focus on biomedical and healthcare applications. She has made internationally recognized contributions, namely in the areas of ontology-based semantic similarity and ontology alignment, winning multiple awards and competitions. She is deeply interested in how human knowledge can be communicated to computers and vice-versa.