Predictions for identifying 1-year seizure recurrence performed significantly better in electroencephalography (EEG) without interictal epileptiform discharges. An automated processing algorithm ...
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 ...
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 ...
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 ...
Please provide your email address to receive an email when new articles are posted on . Researchers at Massachusetts General Hospital and Harvard Medical School have developed machine learning-based ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results