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Abstract

Mental disorders present a significant challenge in healthcare due to the lack of specific biomedical tests and the need for close, continuous monitoring to ensure accurate diagnosis. Recent advances in AI, particularly in Natural Language Processing, show great potential in assessing these conditions. However, there are still significant challenges to translating this potential into the reality of psychiatric practice. In this presentation, I will discuss the work conducted at UFRN on discourse analysis in clinical settings for various disorders. Topics will include: the state of the art in detecting cognitive neuropathies, the search for descriptors that enable the development of explainable diagnostic systems, the construction of neuroscientific models that link speech patterns to neural mechanisms, and the challenges in creating technology that integrates seamlessly with clinical practice.

Speaker Biography

Prof. César Rennó-Costa is an Assistant Professor of Bioinformatics and the Director of the Bioinformatics Multidisciplinary Environment at the Digital Metropolis Institute, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil. His research background lies in computational neuroscience, particularly in modeling biological neural networks, focusing on hippocampal circuits. He has participated in several collaborative projects with US and European institutions. More recently, his work has expanded into applied medical research, including developing digital systems utilizing AI and data science to support public health agencies, mainly focusing on behavioral sciences and computational psychiatry through natural language processing techniques. He currently leads an international network financed by the Newton Fund aimed at developing computational methods for characterizing and identifying mental disorders.