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The paper “Decoding Breast Cancer: Using Radiomics to Non-Invasively Unveil Molecular Subtypes Directly from Mammographic Images” presents a method that uses radiomics to analyze mammographic images and identify distinct molecular subtypes of breast cancer. By extracting and analyzing quantitative features from these images, the study paves the way for potentially Read more…

The international per-review scientific journal Bioengineering has published a special issue dedicated entirely to breast cancer imaging. This special issue was edited by three researchers from the IBEB team: Ana Gouveia, Hugo Ferreira and Nuno Matela. Access is free and can be done through the following link:

Negative symptoms in psychosis are still the hardest to treat and probably multifactorial. Our work has suggested that some can be associated with blood markers, which might in the future open way to a more precise and quick diagnosis and efficient treatment to help patients experiencing psychosis disorders, such as Read more…

A new paper has just been published by researchers from our institute. Take a look at “Artificial intelligence on breast cancer risk prediction” in Elsevier’s Societal Impacts journal!

A new research paper has just been published by researchers from our institute! Take a look at “Breast Cancer Molecular Subtype Prediction: A Mammography-Based AI Approach” (https://www.mdpi.com/2227-9059/12/6/1371)

The molecular subtype of breast cancer is one of the main markers that determines the aggressiveness of the tumor and the therapy to follow. Currently, this characterization is done in a very invasive and painful way through biopsies, a highly specialized, expensive process, prone to errors due to the heterogeneity Read more…