Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

The automatic rule-based recurrence detection algorithm (Auto-Recur), using notes on image reading (positron emission tomography-computed tomography [PET-CT], CT, magnetic resonance imaging [MRI]), ...

Approximately 20% to 30% of men with prostate cancer experience disease recurrence within 5 years of therapeutic intervention. 1 A key challenge in managing these patients is a scarcity of accurate ...

Researchers have developed and validated a machine learning--based method to predict which patients with early-stage melanoma are most likely to experience a cancer recurrence. Most deaths from ...

Machine Learning–Based Analysis of Treatment Sequences Typology in Advanced Non–Small-Cell Lung Cancer Long-Term Survivors Treated With Nivolumab Deep convolutional neural networks were used to ...

Omitting race and ethnicity from colorectal cancer (CRC) recurrence risk prediction models could decrease their accuracy and fairness, particularly for minority groups, potentially leading to ...