Finding the right dose of medication by trial and error can be a painful experience for patients who are already suffering because of their disease. Artificial intelligence can greatly accelerate this process thanks to a new algorithm created by Adrien Coulet, lecturer at the Université de Lorraine and researcher in a joint Inria and Loria team, in collaboration with researchers from Stanford University. By analyzing patients' digital data, this innovative tool can predict in advance whether patients will need a lower dose of medication thus reducing the suffering caused by side effects. This result was published in Nature Scientific Reports.
Predicting future threats on the Internet: Inria, International University of Rabat and Carnegie Mellon University are collaborating on the NATO-funded ThreatPredict project
The goal of ThreatPredict is to improve prediction of cyber security threats using a novel approach that combines artificial intelligence, big data and heterogeneous input data.
The results it produces will make it possible to best prepare for future attacks and limit their impact. It is funded by the North Atlantic Treaty Organisation (NATO) under the Science for Peace and Security (SPS) program.
Inria is pleased to announce the launch of the scikit-learn initiative, whose objective is to speed up, with the support of user companies, the development of this reference software by adding new functionalities. Scikit-learn is a library developed in Python, an object-oriented programming language. It is dedicated to statistical learning (machine learning) and can be used as middleware, especially for prediction tasks.
Groupe PSA and Inria today announced the creation of an OpenLab dedicated to artificial intelligence. The studied areas will include autonomous and intelligent vehicles, mobility services, manufacturing, design development tools, the design itslelf and digital marketing as well as quality and finance.
A year ago, Inria signed an agreement with UNESCO - opening the way to joint actions in favour of the preservation and sharing of software source code, in particular through the Software Heritage project which, for this occasion, launched its website in several language.
Launch of 3d edition of CNIL-INRIA Privacy Award : Nominate a Scientific Article and Promote Privacy Research
The third edition of the CNIL-INRIA "Privacy Protection" Award starts on 16 May 2018. It will reward a scientific paper on privacy and personal data protection published in 2016-2017
The Pl@ntNet application enables, with the help of a smartphone, the real-time identification of plants and the collection and sharing of its observations in order to help with their identification.
Originally only used for the monitoring of rare, exotic or endangered plant species, the application is diversifying and opening up its directory to ornamental plants and plants cultivated in our regions, as well as abroad (North America, South America and the West Indies in particular), thereby answering the main questions of its users and enabling the number of references in the directory to almost double.
Inria announces today the Software Heritage project, an ambitious initiative to collect, organise, preserve, and make easily accessible any already publicly available source code.
Sending messages to our family and friends, paying bills, purchasing goods, accessing entertainment, interacting with the public administration, finding information, booking travels: practically every act of our daily life relies on computers and software to be performed.
That is just the tip of the iceberg: software controls the electronic equipment embedded in the machines we use to travel, communicate, trade and exchange.
Today, Inria announces the launch of SoundCity, a mobile application to measure your personal exposure to noise pollution. The project is supported by the City of Paris smart city initiative and Bernard Jomier, deputy mayor responsible for health, disability, and relations with Paris public hospital system.
Pixyl has developed a new software solution for medical research designed to extract the maximum amount of information contained in MRI brain scans (Magnetic Resonance Imaging). This solution specifically locates, identifies and quantifies, from MRI sequences, a broad range of brain lesions related to pathologies such as multiple sclerosis, brain trauma, cerebrovascular accidents and brain tumours. Pixyl thus opens up new possibilities for the use of these imaging resources whose potential has hitherto remained under-developed in the biotechnology industry.