Snaebjornsson et al. explore a selective vulnerability in cancer elicited by targeting aldolase A, which causes energy imbalance and prevents further metabolic adaptations.

In 2024, important studies highlighted the ongoing global battle against liver cancer, a deadly yet common cancer. Despite advances in treatments, obstacles persist in early detection and equity in healthcare access. The journey towards improving patient outcomes remains bumpy. Gaining insights from failures is critical for effectively tackling this persistent health threat.

A recent study reported the development and validation of the Liver Artificial Intelligence Diagnosis System (LiAIDS), a fully automated system that integrates deep learning for the diagnosis of liver lesions on the basis of contrast-enhanced CT scans and clinical information. This tool improved diagnostic precision, surpassed the accuracy of junior radiologists (and equalled that of senior radiologists) and streamlined patient triage. These advances underscore the potential of artificial intelligence to enhance hepatology care, although challenges to widespread clinical implementation remain.