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Focus on good health and well-being

by   -   January 22, 2021

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.

Davide Bacciu

In the second interview in this series of Meet the Team Leaders from the CLAIRE COVID-19 Initiative, we hear from Davide Bacciu (Università di Pisa).

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.

by   -   January 14, 2021

Guillem Alenya
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.

by   -   January 12, 2021

COVID lesions
The Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE) taskforce on AI & COVID-19 supported the creation of a research group focused on AI-assisted diagnosis of COVID-19 pneumonia. The first results demonstrate the great potential of AI-assisted diagnostic imaging. Furthermore, the impact of the taskforce work is much larger, and it embraces the cross-fertilisation of artificial intelligence (AI) and high-performance computing (HPC): a partnership with rocketing potential for many scientific domains.

by   -   January 6, 2021
Reading diabetes monitor Credit: James Charles
Reading diabetes monitor. Credit: James Charles

A computer vision technology developed by University of Cambridge engineers has now been integrated into a free mobile phone app for regular monitoring of glucose levels in people with diabetes.

The app uses computer vision techniques to read and record the glucose levels, time and date displayed on a typical glucose test via the camera on a mobile phone.

By Joyce Anne Quinto

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   -   December 29, 2020
A computational tool created at Rice University may help pharmaceutical companies expand their ability to investigate the safety of drugs. (Credit: Kavraki Lab/Rice University)

By Mike Williams
AIhub focus issue on good health and well-being
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.

Figure 1: CLAIRE COVID-19 Initiative, topic groups and main outcomes

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.

by   -   December 16, 2020
embroided lungs
Blue and Brown Anatomical Lung Wall Decor. Credit: Hey Paul Studios.

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.

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