The need to analyze personal data to drive business, alongside the requirement to preserve the privacy of data subjects, creates a known tension.
An important challenge for applying machine and deep learning methods in applications where data collection is difficult, or costly is the reduced amount of annotated data.
Precision and expertise are necessary to reach 100% quality in data annotation. The process of selecting image annotators, called HITers at isahit, for projects like iToBoS involves rigorous criteria to ensure the highest quality in final annotations.
Self-attention is the core mechanism behind Transformer models, which have provided state-of-the-art results in various scientific fields (i.e. Natural Language Processing).
What benefits does AI offer digital pathologists? How can it revolutionize the field and what are its biggest challenges?
Tanorexia is the tanning dependence. It is a syndrome related to a physical or psychological dependence on sunbathing or using ultraviolet tanning beds.
Large language models have achieved a good performance on different tasks and different data types. However, they often lack of content fidelity and new context creation. These features could help to generate images in a more personalized way.
The integration of digital technologies, e.g., smartphone apps, has been shown to represent an impactful advancement in training for melanoma diagnosis.1
Expanding the concept of Scaled Dot-Product Attention, Vaswani et al. [1] proposed the multi-head attention mechanism.
Conformal prediction offers a solution in uncertainty quantification and simultaneously provides a method for instance classification.