
FDA Clears AI to Read Breast Ultrasounds
Automating ultrasound analysis could finally break the bottleneck in breast cancer screening.
Discover the newest research about AI innovations in 🎗 Oncology.

Automating ultrasound analysis could finally break the bottleneck in breast cancer screening.

A new AI model predicts kidney cancer survival better than the gold-standard human grading system.

A new machine learning model tackles the biological noise threatening to derail non-invasive cancer testing.

A patient’s fate is often hidden in the messy paragraphs of their medical charts rather than their official disease stage.

Algorithms can now flag the earliest signs of lung cancer, but technology alone cannot fix a broken healthcare pipeline.

By tracking entire patient histories instead of clinical snapshots, a new AI model outperforms traditional cancer staging systems across three countries.

A new ensemble AI model predicts positive surgical margins before breast-conserving surgery, but its performance drop in external testing highlights the ongoing struggle with clinical generalization.

A new multi-center model uses basic clinical data to flag brain metastasis before symptoms appear, challenging the need for expensive, complex biomarkers.

A new foundation model uses baseline CT scans to flag which lung cancer patients are likely to develop life-threatening lung inflammation from immunotherapy.

Deploying AI to halve diagnostic wait times is a massive win, but it risks creating a dangerous bottleneck further down the care pathway.