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Field
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architectures for explainable dual-process computation Design and development of deep neural network architectures and algorithms for the implementation of dual process computation approaches that improve
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. The goal is to contribute broadly to research on applications of AI in medicine, and in particular to the development and validation of novel computational language models, algorithms, and tools
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms
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uses, improving the AI and MRI algorithms, and linking them with information from biological studies on tumour tissue. This project harnesses AI to improve diagnosis and clinical decision-making leading
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interaction and analytics using AI. Key Responsibilities: Development of artificial intelligence (AI) technologies to perform human-robot interaction and analytics System integration of the developed algorithms
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computer vision algorithms to detect clinical interventions performed by nurses and situations of agitation and risk of falling. Volume of data available for the project: Video capture in a hospital
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algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in
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algorithms to combine information on cardiovascular activity obtained from heart sound signals, electrocardiogram, and photoplethysmography. Investigate the inclusion of prior knowledge about the application
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algorithms for free-flying robots in microgravity.; • Implement and validate real-time multi-target tracking techniques.; • Validate the algorithms in simulated scenarios, evaluating robustness and accuracy