Maëlle Moranges

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Maëlle Moranges

Postdoctoral researcher in Neuro-informatics

Bio

I am interested in the contribution of artificial intelligence to medicine to better understand and model cognitive and biological mechanisms. Specializing in neuroinformatics and bioinformatics, I leverage machine learning and data mining to address these challenges.

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Interests

eXplainable AI (XAI)
Machine Learning
Data Mining
Natural Language Processing (NLP)
Data Visualization

Education

PhD in Neuroinformatics

University of Lyon 1
Master Degree in Molecular Bioinformatics

University of Lyon 1
Bachelor degree in Mathematics and Computer Life-Science

University of Lyon 1

Research interests

My research area is artificial intelligence with a multidisciplinary approach. I am particularly interested in understanding the interindividual variability in complex biological phenomena, especially in neuroscience and medicine, through the development of interpretable or explainable AI models. This involves designing innovative computational methodologies that combine machine learning techniques, with data mining approaches. My areas of application are related to health. By collaborating with medical experts, my work aims to design models that not only improve healthcare quality but also provide user-centered explanations tailored to diverse stakeholders, from physicians to patients.

Publications

Maëlle Moranges, Noha Ibrahim, Sihem Amer-Yahia, Olivier Palombi (2024). Decoding student learning in medical education through UNESS platform interactions.

Cite Poster

Maëlle Moranges, Arnaud Fournel, Marc Thévenet, Marc Plantevit, Moustafa Bensafi (2024). Using Exceptional Attributed Subgraph Mining to Explore Interindividual Variability in Odor Pleasantness Processing in the Piriform Cortex and Amygdala. Intelligent Computing.

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Maelle Moranges, Marc Plantevit, Moustafa Bensafi (2023). Peripheral Nervous System Responses to Food Stimuli: Analysis Using Data Science Approaches. Basic Protocols on Emotions, Senses, and Foods.

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Maelle Moranges (2023). Variabilités émotionnelle et neurophysiologique dans la perception olfactive: étude par l’intelligence artificielle.

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Maëlle Moranges, Marc Plantevit, Moustafa Bensafi (2022). Using subgroup discovery to relate odor pleasantness and intensity to peripheral nervous system reactions. IEEE Transactions on Affective Computing.

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