Making machine learning models trustworthy is essential as use of them becomes ubiquitous across society, writes Dr Adrian Byrne of CeADAR.

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...

Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

The core of this method lies in quantum feature mapping, which allows classical data to be mapped into a quantum feature space, enabling classical machine learning algorithms to operate ... complex ...

Colorectal cancer is the second leading cause of cancer death worldwide. If detected early, it can be efficiently treated, ...

Compared to classical algorithms, quantum machine learning demonstrates significant advantages in feature extraction, model training, and predictive inference.

Researchers developed metabolomic aging clocks using machine learning, uncovering links between metabolite profiles, health outcomes, and lifespan.

The Machine Learning in Biomedicine (MLBioMed) research group at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, is currently seeking a highly-motivated postdoctoral ...