On 3 June 2020, the VUB AI Experience Centre published a webinar on the topic of the role of AI in the COVID-19 crisis, focused on macro dynamics predictions in the COVID-19 crisis, explained by micro intentions.
The CLAIRE Covid-19 Initiative would like to share a series of interviews called “Meet the Team Leaders”, in which the team talk about the significant work they have contributed to, lessons learned from this process and the outlook for the challenges ahead. In this post you can watch the first of the interviews, with Emanuela Girardi.
Guillem Alenyà is Director of the Institut de Robòtica i Informàtica Industrial, CSIC-UPC, in Barcelona. His research activities include assistive robotics, robot adaptation, human-robot interactions and grasping of deformables. We spoke about some of the projects he is involved in and his plans for future work.
As part of its second anniversary activities, CLAIRE hosted a webinar presenting the progress and future plans of its COVID-19 taskforce. Entitled, “CLAIRE taskforce for AI and COVID-19: results and next steps”, the webinar was conducted on 15 July 2020 with a focus on the three-month research outcomes in the areas of AI for bioinformatics, drug repurposing, and medical image analysis.
By Mike Williams
When you take a medication, you want to know precisely what it does. Pharmaceutical companies go through extensive testing to ensure that you do. With a new deep learning-based technique created at Rice University’s Brown School of Engineering, they may soon get a better handle on how drugs in development will perform in the human body.
By Gianluca Bontempi, Ricardo Chavarriaga, Hans de Canck, Emanuela Girardi, Holger Hoos and Iarla Kilbane-Dawe
CLAIRE, the Confederation of Laboratories for AI Research in Europe, launched its COVID-19 initiative in March 2020 as the first wave of the pandemic hit the continent. Its objective is to coordinate volunteer efforts of its members to contribute to tackling the effects of the disease. The taskforce was able to quickly gather a group of about 150 researchers, scientists and experts in AI organized in seven topic groups: epidemiological data analysis, mobility data analysis, bioinformatics, medical imaging, social dynamics monitoring, robotics, and scheduling and resource management.
Accurately predicting how an individual’s chronic illness is going to progress is critical to delivering better-personalised, precision medicine. Only with such insight can a clinician and patient plan optimal treatment strategies for intervention and mitigation. Yet there is an enormous challenge in accurately predicting the clinical trajectories of people for chronic health conditions such as cystic fibrosis (CF), cancer, cardiovascular disease and Alzheimer’s disease.