Scaled Dot-Product Attention

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).

AI in Digital Pathology

What benefits does AI offer digital pathologists? How can it revolutionize the field and what are its biggest challenges?

Tanorexia, another face of sun exposure

Tanorexia is the tanning dependence. It is a syndrome related to a physical or psychological dependence on sunbathing or using ultraviolet tanning beds.

Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation

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.

Seeing is Believing: How AI might transform skin cancer education

The integration of digital technologies, e.g., smartphone apps, has been shown to represent an impactful advancement in training for melanoma diagnosis.1

Multi-Head Attention

Expanding the concept of Scaled Dot-Product Attention, Vaswani et al. [1] proposed the multi-head attention mechanism.

Conformal prediction in AI

Conformal prediction offers a solution in uncertainty quantification and simultaneously provides a method for instance classification.

The Crucial Role of Data Annotation in the iToBoS Project

Artificial intelligence (AI) is at its peak right now. And we know its applications in healthcare are numerous. But when it comes to health data labeling, precision is necessary.

iToBoS project presented in PhoenixD Magazine

The iToBoS project was introduced in the second edition of PhoenixD Magazine.

Stratified K-Fold cross-validation for imbalanced datasets

In Machine Learning, a common technique used to train a robust and generalizable model, is cross-validation. It divides the dataset into multiple subsets, where typically one of them is the validation set and the remainder consist the training set.