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Predictive Boolean Network Ensembles – BNeDiction
recurring question at the intersection of artificial intelligence and life sciences
Prediction of response to systemic treatments in hepatocellular carcinoma – SYSTHEC
immunohistochemical analysis as well as artificial intelligence analysis in 140 HCC samples from patients treated
Prediction of cerebral injury secondary to endovascular recanalization of acute ischemic stroke – PRECISE-STROKE
Brain infarction (BI) is the major cause of dependency. TThe occurrence of an hemorrhagic transformation after successful revascularization decrease sby 20% the rate of functional recovery at 3 months. Experimental studies suggest that thrombo-inflammatory mechanisms contribute to HT but their mitigation has yet to prove its efficacy. We aim to characterize individual predictive biomarkers of HT to propose a tailored management of this complication in patients.
Prediction and Intelligent Control with Simulation and Numerical Optimization – PRECCISION
PRECCISION project aims at bringing scientific and technical solutions to improve building energy management systems. We will develop new methods and tools to analyze in real-time the building’s energy behavior and to control it, either by acting directly on the systems configuration or by providing the user or the building manager with useful information about the building state.
Prediction Of Relapse Through Artificial Intelligence and multi-omics after allogeneic hematopoietic stem cell transplantation – PORTRAIT
Allogeneic hematopoietic stem cell transplantation (alloHSCT) is a curative therapy for hematologic malignancies through the graft-versus-tumor effect. Yet relapse remains the leading cause of death after transplant. Mechanisms include T cell exhaustion, Treg expansion, microbiota and metabolic alterations. No biomarker reliably predicts relapse. This project aims to identify clinical, immune and metabolomic signatures from a large cohort to build a predictive scoring tool.
Predicting the biodiversity of reef fishes – FISH-PREDICT
developing new algorithms and methods in Artificial Intelligence (AI) integrating multiple sources of information
Predicting and detecting anomalies in a moving crowd without interruption – OKLOS
in image / video processing and in Artificial Intelligence, develops algorithms for the analysis of crowd
Predicting Inner Wood Defects from Outer Bark Features – WoodSeer
A trained expert can detect subtle variations in bark roughness to reveal the presence of underlying defects. Could AI, utilizing 3D data, replicate this ability and potentially reconstruct the hidden defect?
Precision AgriVoltaics for Carbon Neutrality Enhanced Production and Reduced Environmental Impact in Greenhouse – PAVER
of this project is to design and develop an intelligent, robust, feasible and sustainable AIoT-Agrovoltaic [...] software modules based on advanced artificial intelligence algorithms to jointly control and optimize:
Practical algorithms for ontology-based data access – PAGODA
L’interrogation de données en présence d’ontologie est un nouveau paradigme dans la gestion de données qui vise à exploiter des connaissances sémantiques décrites par une ontologie afin d’améliorer les réponses aux requêtes. L’objectif de ce projet est de proposer de nouveaux algorithmes d'interrogation en présence d'ontologie qui passent à l'échelle ainsi que de nouvelles méthodes pragmatiques pour gérer de façon raisonnée les données incohérentes. <br />
