iToBoS project in the Mobile World Congress 2024

29/02/2024.

iToBoS members attended the Mobile World Congress 2024, held in Barcelona, from February 26th to February 29th.

iToBoS liquid lens nominated for PRISM Award

28/02/2024.

Every year, the international society for optics and photonics (SPIE) recognizes innovative companies with the Prism Award.

ELM-75 liquid lens presented at Photonics West

26/02/2024.

Every year end of January, the international society for optics and photonics (SPIE) hosts Photonics West, the world’s largest trade show for optics, in San Francisco.

HPV and squamous cell carcinoma

23/02/2024.

Non-melanoma skin cancers, including squamous cell carcinoma (SCC), represent the most common form of cancer in Caucasians, with a continuing increase in incidence worldwide.

Ethical AI at MPNE Consensus Data

21/02/2024.

Trilateral Research recently attended the MPNE Consensus Data event in the framework of iToBoS project, held in Berlin between January 31st and February 2nd, 2024.

Data security and privacy at MPNE consensus 2024

19/02/2024.

IBM recently took part in the MPNE Consensus conference in Berlin, Germany.

iToBoS project was presented at “XII Reunión Anual del Grupo Español de e-Dermatología e imagen (GEDEI)”

16/02/2024.

The iToBoS project was presented at “XII Reunión Anual del Grupo Español de e-Dermatología e imagen (GEDEI)”, that took place in Madrid, Spain, on February 16th, 2024.

Dicing with data: the risks, benefits, tensions and tech of health data in the iToBoS project

14/02/2024.

Partners in the iToBoS consortium recently had their work published in a peer reviewed scientific journal, entitled Frontiers in Digital Health.

Reflections about data sharing in the healthcare sector

12/02/2024.

Actors from different sectors, backgrounds and involvement with the acquisition, access and management of health data met in Berlin in the context of the MPNE 2024 Consensus in the framework of the iToBoS project.

A step into Machine Unlearning

10/02/2024.

What is Machine Unlearning? Basically, this concept represents the opposite of machine learning: it serves to make a model unlearn or forget.