Opportunities and Challenges in Artificial Intelligence Skin Image Analyses Using Total Body Photography

In the last decade the application of artificial intelligence (AI) algorithms in dermatology to classify skin lesions, particularly melanoma, has advanced rapidly.

HPV and squamous cell carcinoma

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

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

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

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

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

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.

Perspectives for Generative AI at MPNE Consensus on Data Workshop

Berlin, 1/02/2024.

Presentation of the perspectives of generative Artificial Intelligence in melanoma at the MPNEconsensus 2024 by the iToBoS partner Leibniz University Hannover.

Transformers in Dermoscopic Image Classification

Dermoscopy is a powerful method used in dermatology to analyze the features of skin lesions.

Semi-Supervised Learning

Semi-supervised learning is a type of machine learning paradigm that falls between supervised and unsupervised learning.